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[ Intro ] [ full-2 ] [ medium-1000 ]
[ medium-10000 ] [ medium-2000 ] [ medium-3000 ]
[ medium-4000 ] [ medium-5000 ] [ medium-6000 ]
[ medium-6000a-zero ] [ medium-6000a ] [ medium-6000b ]
[ medium-7000 ] [ medium-8000 ] [ medium-9000 ]
[ medium.2-1000 ] [ medium.2-10000 ] [ medium.2-2000 ]
[ medium.2-3000 ] [ medium.2-4000 ] [ medium.2-5000 ]
[ medium.2-6000 ] [ medium.2-7000 ] [ medium.2-8000 ]
[ medium.2-9000 ] [ optimal-1 ] [ optimal-1a ]
[ optimal-2 ] [ optimal-3 ] [ optimal-4 ]
[ optimal-5 ] [ optimal-5a ] [ optimal-6 ]
[ param-learn ] [ param-momentum ] [ parameter-matrix ]
[ paramselection-hidden ] [ short-1000 ] [ short-2000 ]
[ short-3000 ] [ short-4000 ] [ short-5000 ]
[ short-6000 ] [ short.2-1000 ] [ short.2-2000 ]
[ short.2-3000 ] [ short.2-4000 ] [ short.2-5000 ]
[ short.2-6000 ] [ simple-10000 ] [ simple-100000 ]
[ simple-2000 ] [ simple-5000 ]

[ Up: Report ] 

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	-0.09983108003663288	-0.6231975499192959	age
Hidden Weights:
	-0.681222936258892	0.5219340846596099
	0.33635102014607265	-0.6014201907181642
		>50K		<=50K

Error sum for iteration 100 = 56.513464476590094

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.3985895318625496	-0.6233989366139979	age
Hidden Weights:
	-0.8382458148152786	1.020789659355068
	0.33633940441274346	-0.6014083165474674
		>50K		<=50K

Error sum for iteration 200 = 56.511707208594295

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.43345122595427305	-0.6235919329075628	age
Hidden Weights:
	-0.8377346464495248	1.0202731709531507
	0.33632811345851593	-0.6013970237073292
		>50K		<=50K

Error sum for iteration 300 = 56.51110021606716

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.45415949749616885	-0.6237841787061572	age
Hidden Weights:
	-0.8374329139564923	1.0199696379406564
	0.3363168655364136	-0.6013857745966179
		>50K		<=50K

Error sum for iteration 400 = 56.510791929940986

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.4689663112434429	-0.6239757144990429	age
Hidden Weights:
	-0.8372173787064077	1.0197531933329942
	0.3363056584574512	-0.6013745666347858
		>50K		<=50K

Error sum for iteration 500 = 56.5106051715453

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.48050930269269304	-0.6241665570496338	age
Hidden Weights:
	-0.8370493192053075	1.0195845840375597
	0.3362944913044033	-0.601363398773418
		>50K		<=50K

Error sum for iteration 600 = 56.510479815423636

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.48997532916250014	-0.62435671667705	age
Hidden Weights:
	-0.836911421850443	1.0194463178620223
	0.33628336350595567	-0.6013522703802701
		>50K		<=50K

Error sum for iteration 700 = 56.51038980623431

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.49800172206344695	-0.6245462011591494	age
Hidden Weights:
	-0.8367944177446199	1.019329048905726
	0.3362722746273934	-0.601341180987213
		>50K		<=50K

Error sum for iteration 800 = 56.51032201360639

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5049707669367138	-0.6247350170430368	age
Hidden Weights:
	-0.8366927562463103	1.0192271878334422
	0.3362612243002709	-0.601330130205404
		>50K		<=50K

Error sum for iteration 900 = 56.510269099023915

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5111299829664809	-0.6249231701918719	age
Hidden Weights:
	-0.8366028466838737	1.019137122385965
	0.3362502121930664	-0.6013191176899211
		>50K		<=50K

Error sum for iteration 1000 = 56.51022663816708

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5166488966975878	-0.6251106660475533	age
Hidden Weights:
	-0.8365222309676221	1.0190563814732847
	0.33623923799704647	-0.6013081431227443
		>50K		<=50K

Error sum for iteration 1100 = 56.51019180431793

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5216487375224536	-0.6252975097703242	age
Hidden Weights:
	-0.8364491516936424	1.0189831993914926
	0.33622830141878546	-0.6012972062037368
		>50K		<=50K

Error sum for iteration 1200 = 56.51016270660016

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5262192152954155	-0.6254837063189211	age
Hidden Weights:
	-0.836382308459753	1.0189162701888217
	0.33621740217583973	-0.6012863066454337
		>50K		<=50K

Error sum for iteration 1300 = 56.51013803209244

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.530428588450089	-0.6256692604993731	age
Hidden Weights:
	-0.8363207117705034	1.018854600517533
	0.33620653999415523	-0.6012754441699211
		>50K		<=50K

Error sum for iteration 1400 = 56.51011684056515

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5343300061074104	-0.6258541769964007	age
Hidden Weights:
	-0.8362635910695835	1.0187974170629794
	0.3361957146063394	-0.601264618506779
		>50K		<=50K

Error sum for iteration 1500 = 56.51009844092346

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5379656658706901	-0.6260384603941742	age
Hidden Weights:
	-0.8362103344748288	1.0187441059156332
	0.3361849257505384	-0.601253829391787
		>50K		<=50K

Error sum for iteration 1600 = 56.5100823137682

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5413696324289942	-0.6262221151908162	age
Hidden Weights:
	-0.8361604479368154	1.018694171502363
	0.33617417316970094	-0.6012430765659145
		>50K		<=50K

Error sum for iteration 1700 = 56.51006806116095

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5445698035431114	-0.6264051458088578	age
Hidden Weights:
	-0.8361135267576767	1.0186472079578568
	0.33616345661096386	-0.6012323597746555
		>50K		<=50K

Error sum for iteration 1800 = 56.51005537305867

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5475893154200079	-0.6265875566026957	age
Hidden Weights:
	-0.8360692352340134	1.0186028786690124
	0.3361527758252756	-0.6012216787676933
		>50K		<=50K

Error sum for iteration 1900 = 56.51004400430027

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5504475690580856	-0.6267693518644596	age
Hidden Weights:
	-0.8360272917910156	1.0185609013415973
	0.33614213056709147	-0.6012110332982107
		>50K		<=50K

Error sum for iteration 2000 = 56.51003375846747

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.553160994015261	-0.6269505358283997	age
Hidden Weights:
	-0.8359874579200202	1.0185210368904714
	0.33613152059412715	-0.6012004231229842
		>50K		<=50K

Error sum for iteration 2100 = 56.510024476336525

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5557436263273171	-0.6271311126742914	age
Hidden Weights:
	-0.8359495298076797	1.0184830810348633
	0.336120945667147	-0.6011898480019804
		>50K		<=50K

Error sum for iteration 2200 = 56.51001602746569

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5582075523517122	-0.6273110865304691	age
Hidden Weights:
	-0.835913331906813	1.0184468578446289
	0.33611040554976945	-0.6011793076981238
		>50K		<=50K

Error sum for iteration 2300 = 56.51000830396918

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5605632542246346	-0.6274904614759381	age
Hidden Weights:
	-0.8358787119320522	1.0184122147175532
	0.33609990000845213	-0.6011688019772897
		>50K		<=50K

Error sum for iteration 2400 = 56.510001215839814

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.562819882003303	-0.6276692415424688	age
Hidden Weights:
	-0.835845536917129	1.018379018423007
	0.33608942881232884	-0.6011583306079803
		>50K		<=50K

Error sum for iteration 2500 = 56.50999468739062

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5649854704128096	-0.6278474307162576	age
Hidden Weights:
	-0.8358136900744154	1.0183471519509908
	0.33607899173311084	-0.601147893361451
		>50K		<=50K

Error sum for iteration 2600 = 56.50998865451338

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5670671132050498	-0.6280250329392507	age
Hidden Weights:
	-0.835783068268276	1.0183165119775057
	0.3360685885449934	-0.6011374900114373
		>50K		<=50K

Error sum for iteration 2700 = 56.509983062544975

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5690711047072535	-0.6282020521104027	age
Hidden Weights:
	-0.8357535799636644	1.0182870068068133
	0.33605821902462746	-0.6011271203343029
		>50K		<=50K

Error sum for iteration 2800 = 56.50997786458782

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5710030557033193	-0.6283784920869417	age
Hidden Weights:
	-0.8357251435464593	1.0182585546869103
	0.3360478829510267	-0.6011167841086312
		>50K		<=50K

Error sum for iteration 2900 = 56.509973020178

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5728679890401747	-0.6285543566852638	age
Hidden Weights:
	-0.8356976859374425	1.0182310824195944
	0.33603758010551427	-0.6011064811154545
		>50K		<=50K

Error sum for iteration 3000 = 56.50996849421687

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5746704190737172	-0.6287296496818262	age
Hidden Weights:
	-0.8356711414404666	1.0182045242054845
	0.33602731027170374	-0.6010962111381337
		>50K		<=50K

Error sum for iteration 3100 = 56.509964256110244

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.576414418126426	-0.6289043748141107	age
Hidden Weights:
	-0.8356454507787215	1.0181788206777391
	0.3360170732354204	-0.6010859739622169
		>50K		<=50K

Error sum for iteration 3200 = 56.509960279067656

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5781036724251581	-0.6290785357812206	age
Hidden Weights:
	-0.8356205602834664	1.018153918088792
	0.3360068687846556	-0.6010757693755331
		>50K		<=50K

Error sum for iteration 3300 = 56.50995653952836

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5797415294568516	-0.6292521362447078	age
Hidden Weights:
	-0.8355964212071035	1.018129767621708
	0.33599669670954685	-0.6010655971679106
		>50K		<=50K

Error sum for iteration 3400 = 56.50995301668869

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5813310382757296	-0.6294251798292527	age
Hidden Weights:
	-0.8355729891384478	1.0181063248040196
	0.33598655680233563	-0.6010554571314652
		>50K		<=50K

Error sum for iteration 3500 = 56.50994969210992

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5828749839850788	-0.6295976701233321	age
Hidden Weights:
	-0.8355502235023323	1.0180835490062816
	0.33597644885729505	-0.6010453490602836
		>50K		<=50K

Error sum for iteration 3600 = 56.50994654939114

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5843759173759241	-0.6297696106797348	age
Hidden Weights:
	-0.8355280871295598	1.018061403010957
	0.33596637267079693	-0.6010352727505176
		>50K		<=50K

Error sum for iteration 3700 = 56.50994357389492

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5858361805167664	-0.6299410050161658	age
Hidden Weights:
	-0.8355065458854336	1.01803985264023
	0.33595632804113673	-0.601025228000401
		>50K		<=50K

Error sum for iteration 3800 = 56.50994075251702

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5872579289409599	-0.6301118566158532	age
Hidden Weights:
	-0.8354855683476766	1.0180188664332095
	0.33594631476857884	-0.6010152146101011
		>50K		<=50K

Error sum for iteration 3900 = 56.509938073489245

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5886431509606377	-0.6302821689279441	age
Hidden Weights:
	-0.8354651255260537	1.0179984153649668
	0.33593633265540895	-0.6010052323816413
		>50K		<=50K

Error sum for iteration 4000 = 56.509935526214925

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5899936845424893	-0.6304519453682476	age
Hidden Weights:
	-0.8354451906172636	1.0179784726009433
	0.3359263815057355	-0.6009952811190784
		>50K		<=50K

Error sum for iteration 4100 = 56.50993310112522

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5913112321060097	-0.6306211893195613	age
Hidden Weights:
	-0.8354257387900329	1.0179590132816656
	0.33591646112556073	-0.6009853606283295
		>50K		<=50K

Error sum for iteration 4200 = 56.50993078955825

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5925973735437683	-0.6307899041321549	age
Hidden Weights:
	-0.8354067469960387	1.0179400143332058
	0.3359065713227751	-0.6009754707171643
		>50K		<=50K

Error sum for iteration 4300 = 56.50992858365326

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5938535777140442	-0.6309580931242348	age
Hidden Weights:
	-0.8353881938028651	1.0179214542999957
	0.3358967119070626	-0.6009656111951721
		>50K		<=50K

Error sum for iteration 4400 = 56.50992647626058

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5950812126162682	-0.6311257595825038	age
Hidden Weights:
	-0.8353700592462359	1.0179033131966428
	0.33588688268991057	-0.6009557818737533
		>50K		<=50K

Error sum for iteration 4500 = 56.509924460862926

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5962815544262389	-0.6312929067623982	age
Hidden Weights:
	-0.8353523246986397	1.0178855723763873
	0.3358770834845661	-0.600945982566121
		>50K		<=50K

Error sum for iteration 4600 = 56.509922531506575

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5974557955411898	-0.6314595378887111	age
Hidden Weights:
	-0.8353349727524743	1.0178682144140476
	0.335867314106059	-0.6009362130872196
		>50K		<=50K

Error sum for iteration 4700 = 56.50992068274175

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5986050517622584	-0.6316256561558969	age
Hidden Weights:
	-0.8353179871155838	1.017851223001353
	0.33585757437115177	-0.6009264732536868
		>50K		<=50K

Error sum for iteration 4800 = 56.50991890957084

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.5997303687229066	-0.6317912647285071	age
Hidden Weights:
	-0.8353013525178418	1.0178345828534123
	0.3358478640983281	-0.6009167628838982
		>50K		<=50K

Error sum for iteration 4900 = 56.50991720740163

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6008327276564895	-0.6319563667415797	age
Hidden Weights:
	-0.8352850546272561	1.0178182796246762
	0.3358381831077082	-0.6009070817979666
		>50K		<=50K

Error sum for iteration 5000 = 56.509915572007664

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6019130505829537	-0.6321209653010506	age
Hidden Weights:
	-0.8352690799745532	1.0178022998333727
	0.3358285312210993	-0.6008974298176505
		>50K		<=50K

Error sum for iteration 5100 = 56.50991399949225

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6029722049831673	-0.6322850634840554	age
Hidden Weights:
	-0.8352534158852007	1.0177866307934373
	0.33581890826191835	-0.6008878067662861
		>50K		<=50K

Error sum for iteration 5200 = 56.5099124862568

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6040110080208503	-0.6324486643394543	age
Hidden Weights:
	-0.8352380504180154	1.017771260553032
	0.33580931405524767	-0.6008782124689127
		>50K		<=50K

Error sum for iteration 5300 = 56.50991102897282

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6050302303635526	-0.6326117708879713	age
Hidden Weights:
	-0.8352229723095023	1.0177561778388275
	0.33579974842776594	-0.6008686467521023
		>50K		<=50K

Error sum for iteration 5400 = 56.50990962455732

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6060305996473849	-0.6327743861227496	age
Hidden Weights:
	-0.8352081709235123	1.0177413720055235
	0.3357902112076844	-0.6008591094441325
		>50K		<=50K

Error sum for iteration 5500 = 56.509908270149985

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.607012803624771	-0.6329365130096091	age
Hidden Weights:
	-0.8351936362054108	1.0177268329900382
	0.3357807022248221	-0.600849600374706
		>50K		<=50K

Error sum for iteration 5600 = 56.50990696309413

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6079774930295232	-0.6330981544873725	age
Hidden Weights:
	-0.8351793586403762	1.0177125512696967
	0.3357712213104935	-0.6008401193750635
		>50K		<=50K

Error sum for iteration 5700 = 56.509905700918566

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6089252841888662	-0.6332593134682497	age
Hidden Weights:
	-0.8351653292153864	1.0176985178241358
	0.33576176829755255	-0.6008306662781295
		>50K		<=50K

Error sum for iteration 5800 = 56.50990448132107

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6098567614091212	-0.633419992838205	age
Hidden Weights:
	-0.835151539384482	1.0176847241005804
	0.3357523430203621	-0.6008212409181207
		>50K		<=50K

Error sum for iteration 5900 = 56.50990330215526

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.610772479157911	-0.6335801954572147	age
Hidden Weights:
	-0.8351379810369892	1.0176711619819978
	0.33574294531476295	-0.6008118431308562
		>50K		<=50K

Error sum for iteration 6000 = 56.50990216141686

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.611672964063579	-0.6337399241595705	age
Hidden Weights:
	-0.8351246464684257	1.017657823757945
	0.3357335750180527	-0.600802472753617
		>50K		<=50K

Error sum for iteration 6100 = 56.50990105723245

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6125587167497601	-0.6338991817542027	age
Hidden Weights:
	-0.835111528353759	1.0176447020978459
	0.3357242319690025	-0.600793129625192
		>50K		<=50K

Error sum for iteration 6200 = 56.50989998784858

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6134302135211825	-0.6340579710250436	age
Hidden Weights:
	-0.8350986197228673	1.0176317900263625
	0.33571491600777725	-0.6007838135856791
		>50K		<=50K

Error sum for iteration 6300 = 56.509898951622745

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6142879079149738	-0.6342162947312662	age
Hidden Weights:
	-0.8350859139379492	1.017619080900834
	0.33570562697597367	-0.6007745244766711
		>50K		<=50K

Error sum for iteration 6400 = 56.509897947014586

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6151322321302628	-0.6343741556076619	age
Hidden Weights:
	-0.835073404672659	1.0176065683903395
	0.33569636471658476	-0.6007652621410834
		>50K		<=50K

Error sum for iteration 6500 = 56.50989697257797

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6159635983471403	-0.6345315563648215	age
Hidden Weights:
	-0.8350610858929425	1.0175942464565302
	0.3356871290739767	-0.6007560264232596
		>50K		<=50K

Error sum for iteration 6600 = 56.50989602695384

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.616782399945142	-0.6346884996895238	age
Hidden Weights:
	-0.8350489518392447	1.0175821093358095
	0.33567791989387186	-0.6007468171689084
		>50K		<=50K

Error sum for iteration 6700 = 56.50989510886401

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.617589012630527	-0.6348449882450119	age
Hidden Weights:
	-0.8350369970100961	1.0175701515229003
	0.3356687370233849	-0.6007376342250484
		>50K		<=50K

Error sum for iteration 6800 = 56.50989421710498

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6183837954802055	-0.6350010246711737	age
Hidden Weights:
	-0.8350252161468712	1.01755836775561
	0.33565958031087645	-0.6007284774401236
		>50K		<=50K

Error sum for iteration 6900 = 56.509893350542576

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6191670919096267	-0.6351566115848851	age
Hidden Weights:
	-0.8350136042197286	1.017546753000733
	0.33565044960606966	-0.6007193466638501
		>50K		<=50K

Error sum for iteration 7000 = 56.5098925081074

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6199392305712318	-0.6353117515803155	age
Hidden Weights:
	-0.8350021564144694	1.0175353024408724
	0.33564134476000446	-0.600710241747126
		>50K		<=50K

Error sum for iteration 7100 = 56.50989168878942

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6207005261894574	-0.6354664472290957	age
Hidden Weights:
	-0.8349908681203754	1.017524011462331
	0.33563226562499093	-0.6007011625422277
		>50K		<=50K

Error sum for iteration 7200 = 56.50989089163501

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6214512803374077	-0.635620701080728	age
Hidden Weights:
	-0.8349797349188979	1.0175128756437002
	0.33562321205458034	-0.6006921089028309
		>50K		<=50K

Error sum for iteration 7300 = 56.50989011574218

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6221917821600632	-0.6357745156626743	age
Hidden Weights:
	-0.8349687525730929	1.0175018907453468
	0.33561418390360237	-0.6006830806836778
		>50K		<=50K

Error sum for iteration 7400 = 56.50988936025729

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.622922309048533	-0.6359278934807321	age
Hidden Weights:
	-0.8349579170178006	1.0174910526995808
	0.33560518102813824	-0.6006740777407756
		>50K		<=50K

Error sum for iteration 7500 = 56.50988862437252

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6236431272691461	-0.6360808370192433	age
Hidden Weights:
	-0.8349472243504504	1.0174803576014027
	0.33559620328548795	-0.6006650999314536
		>50K		<=50K

Error sum for iteration 7600 = 56.50988790732157

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6243544925508749	-0.6362333487413298	age
Hidden Weights:
	-0.8349366708225021	1.0174698017000317
	0.3355872505341402	-0.6006561471142093
		>50K		<=50K

Error sum for iteration 7700 = 56.50988720837847

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6250566506346567	-0.6363854310891734	age
Hidden Weights:
	-0.8349262528314543	1.0174593813907606
	0.33557832263380577	-0.6006472191487322
		>50K		<=50K

Error sum for iteration 7800 = 56.50988652685372

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6257498377872195	-0.6365370864841945	age
Hidden Weights:
	-0.8349159669133064	1.017449093207548
	0.3355694194453746	-0.6006383158958706
		>50K		<=50K

Error sum for iteration 7900 = 56.50988586209287

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6264342812822998	-0.6366883173273317	age
Hidden Weights:
	-0.8349058097355655	1.017438933815955
	0.33556054083090897	-0.6006294372176413
		>50K		<=50K

Error sum for iteration 8000 = 56.50988521347386

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6271101998517721	-0.6368391259992758	age
Hidden Weights:
	-0.8348957780906455	1.0174289000065326
	0.3355516866536316	-0.6006205829773468
		>50K		<=50K

Error sum for iteration 8100 = 56.50988458040519

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6277778041086779	-0.6369895148606948	age
Hidden Weights:
	-0.8348858688897131	1.0174189886886673
	0.33554285677789675	-0.6006117530392604
		>50K		<=50K

Error sum for iteration 8200 = 56.50988396232414

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6284372969444437	-0.6371394862524524	age
Hidden Weights:
	-0.834876079156862	1.0174091968847876
	0.3355340510692059	-0.6006029472688826
		>50K		<=50K

Error sum for iteration 8300 = 56.50988335869485

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6290888739021101	-0.6372890424958384	age
Hidden Weights:
	-0.8348664060237014	1.0173995217248821
	0.33552526939417265	-0.6005941655327938
		>50K		<=50K

Error sum for iteration 8400 = 56.50988276900671

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6297327235272643	-0.6374381858927757	age
Hidden Weights:
	-0.8348568467241727	1.0173899604414045
	0.3355165116205032	-0.6005854076987671
		>50K		<=50K

Error sum for iteration 8500 = 56.50988219277324

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6303690276981647	-0.6375869187259736	age
Hidden Weights:
	-0.8348473985898072	1.017380510364402
	0.3355077776170425	-0.6005766736354952
		>50K		<=50K

Error sum for iteration 8600 = 56.50988162953031

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6309979619367948	-0.6377352432593452	age
Hidden Weights:
	-0.8348380590451263	1.017371168917002
	0.3354990672536667	-0.6005679632129352
		>50K		<=50K

Error sum for iteration 8700 = 56.50988107883527

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6316196957017883	-0.6378831617379769	age
Hidden Weights:
	-0.8348288256033874	1.0173619336111506
	0.33549038040135987	-0.6005592763020595
		>50K		<=50K

Error sum for iteration 8800 = 56.50988054026499

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6322343926647827	-0.6380306763884493	age
Hidden Weights:
	-0.8348196958625318	1.0173528020435272
	0.3354817169321394	-0.6005506127748215
		>50K		<=50K

Error sum for iteration 8900 = 56.50988001341558

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6328422109712133	-0.6381777894190864	age
Hidden Weights:
	-0.8348106675013979	1.017343771891741
	0.3354730767190815	-0.6005419725042943
		>50K		<=50K

Error sum for iteration 9000 = 56.509879497900826

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6334433034864083	-0.638324503020051	age
Hidden Weights:
	-0.8348017382761034	1.0173348409107803
	0.33546445963628946	-0.6005333553645802
		>50K		<=50K

Error sum for iteration 9100 = 56.50987899335193

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6340378180283235	-0.6384708193635991	age
Hidden Weights:
	-0.8347929060166669	1.017326006929537
	0.3354558655589111	-0.6005247612308103
		>50K		<=50K

Error sum for iteration 9200 = 56.509878499414974

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.634625897587506	-0.6386167406043267	age
Hidden Weights:
	-0.83478416862377	1.0173172678476339
	0.33544729436308346	-0.6005161899791431
		>50K		<=50K

Error sum for iteration 9300 = 56.509878015752044

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6352076805351771	-0.6387622688792244	age
Hidden Weights:
	-0.8347755240657394	1.0173086216324019
	0.335438745925959	-0.6005076414867722
		>50K		<=50K

Error sum for iteration 9400 = 56.50987754203943

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6357833008202788	-0.6389074063080056	age
Hidden Weights:
	-0.8347669703756594	1.0173000663159193
	0.33543022012569096	-0.6004991156317503
		>50K		<=50K

Error sum for iteration 9500 = 56.50987707796648

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6363528881560632	-0.6390521549932073	age
Hidden Weights:
	-0.834758505648644	1.0172915999923866
	0.3354217168413673	-0.6004906122932222
		>50K		<=50K

Error sum for iteration 9600 = 56.50987662323586

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6369165681969418	-0.6391965170204343	age
Hidden Weights:
	-0.8347501280392424	1.0172832208154734
	0.33541323595311323	-0.6004821313511962
		>50K		<=50K

Error sum for iteration 9700 = 56.50987617756229

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6374744627062089	-0.6393404944585174	age
Hidden Weights:
	-0.8347418357590057	1.017274926995852
	0.3354047773419749	-0.6004736726867747
		>50K		<=50K

Error sum for iteration 9800 = 56.50987574067197

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6380266897151959	-0.6394840893596826	age
Hidden Weights:
	-0.8347336270741544	1.0172667167989249
	0.33539634088996806	-0.6004652361819117
		>50K		<=50K

Error sum for iteration 9900 = 56.50987531230224

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6385733636743632	-0.6396273037596742	age
Hidden Weights:
	-0.834725500303354	1.0172585885425665
	0.3353879264799972	-0.6004568217195891
		>50K		<=50K

Error sum for iteration 10000 = 56.509874892200685

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6391145955968529	-0.6397701396780797	age
Hidden Weights:
	-0.8347174538156403	1.0172505405950651
	0.3353795339959413	-0.6004484291836715
		>50K		<=50K

Error sum for iteration 10100 = 56.50987448012522

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6396504931948057	-0.6399125991183631	age
Hidden Weights:
	-0.8347094860284073	1.0172425713730664
	0.3353711633226042	-0.6004400584589326
		>50K		<=50K

Error sum for iteration 10200 = 56.509874075842525

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6401811610091208	-0.6400546840681167	age
Hidden Weights:
	-0.8347015954055355	1.017234679339762
	0.3353628143456786	-0.6004317094310363
		>50K		<=50K

Error sum for iteration 10300 = 56.5098736791289

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6407067005327621	-0.6401963964991907	age
Hidden Weights:
	-0.8346937804555548	1.017226863003001
	0.3353544869517584	-0.6004233819866055
		>50K		<=50K

Error sum for iteration 10400 = 56.50987328976902

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6412272103282084	-0.6403377383678793	age
Hidden Weights:
	-0.8346860397299433	1.0172191209136148
	0.3353461810283064	-0.6004150760130874
		>50K		<=50K

Error sum for iteration 10500 = 56.50987290755543

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6417427861394057	-0.6404787116150508	age
Hidden Weights:
	-0.8346783718214908	1.0172114516637674
	0.33533789646371565	-0.6004067913988681
		>50K		<=50K

Error sum for iteration 10600 = 56.509872532288874

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6422535209981114	-0.6406193181663914	age
Hidden Weights:
	-0.8346707753627511	1.0172038538854185
	0.3353296331472516	-0.6003985280332083
		>50K		<=50K

Error sum for iteration 10700 = 56.509872163777175

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6427595053256357	-0.6407595599324346	age
Hidden Weights:
	-0.8346632490245248	1.0171963262487853
	0.33532139096898755	-0.6003902858061709
		>50K		<=50K

Error sum for iteration 10800 = 56.5098718018353

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6432608270295324	-0.6408994388088283	age
Hidden Weights:
	-0.8346557915144822	1.0171888674609642
	0.33531316981991155	-0.6003820646086788
		>50K		<=50K

Error sum for iteration 10900 = 56.50987144628535

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6437575715960913	-0.6410389566763987	age
Hidden Weights:
	-0.8346484015757863	1.0171814762645963
	0.33530496959182454	-0.6003738643325601
		>50K		<=50K

Error sum for iteration 11000 = 56.5098710969549

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6442498221785091	-0.6411781154014567	age
Hidden Weights:
	-0.8346410779858162	1.0171741514365353
	0.3352967901773606	-0.6003656848704805
		>50K		<=50K

Error sum for iteration 11100 = 56.50987075367896

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6447376596810279	-0.6413169168357373	age
Hidden Weights:
	-0.8346338195549062	1.0171668917866201
	0.3352886314699717	-0.6003575261158803
		>50K		<=50K

Error sum for iteration 11200 = 56.50987041629698

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6452211628394088	-0.6414553628167645	age
Hidden Weights:
	-0.8346266251252223	1.0171596961565172
	0.33528049336398175	-0.6003493879630414
		>50K		<=50K

Error sum for iteration 11300 = 56.50987008465554

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6457004082978334	-0.6415934551678348	age
Hidden Weights:
	-0.8346194935695737	1.017152563418581
	0.3352723757544822	-0.6003412703070523
		>50K		<=50K

Error sum for iteration 11400 = 56.50986975860541

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6461754706823365	-0.641731195698235	age
Hidden Weights:
	-0.8346124237903862	1.0171454924747971
	0.33526427853733526	-0.6003331730438608
		>50K		<=50K

Error sum for iteration 11500 = 56.50986943800318

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6466464226711578	-0.6418685862033491	age
Hidden Weights:
	-0.8346054147186592	1.0171384822556913
	0.3352562016092871	-0.60032509607008
		>50K		<=50K

Error sum for iteration 11600 = 56.50986912270976

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6471133350619728	-0.6420056284649179	age
Hidden Weights:
	-0.8345984653129688	1.0171315317194591
	0.3352481448677837	-0.6003170392831971
		>50K		<=50K

Error sum for iteration 11700 = 56.5098688125914

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6475762768361811	-0.6421423242510242	age
Hidden Weights:
	-0.8345915745585385	1.0171246398509026
	0.3352401082111063	-0.6003090025814981
		>50K		<=50K

Error sum for iteration 11800 = 56.50986850751839

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6480353152207221	-0.6422786753162788	age
Hidden Weights:
	-0.8345847414663254	1.0171178056605876
	0.3352320915382722	-0.6003009858640198
		>50K		<=50K

Error sum for iteration 11900 = 56.50986820736545

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6484905157470319	-0.6424146834019828	age
Hidden Weights:
	-0.8345779650721824	1.0171110281839812
	0.33522409474907244	-0.6002929890305174
		>50K		<=50K

Error sum for iteration 12000 = 56.50986791201197

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6489419423075787	-0.6425503502362757	age
Hidden Weights:
	-0.8345712444359858	1.0171043064805902
	0.33521611774407833	-0.6002850119815579
		>50K		<=50K

Error sum for iteration 12100 = 56.509867621340426

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6493896572101298	-0.6426856775342131	age
Hidden Weights:
	-0.8345645786408762	1.0170976396332123
	0.3352081604245707	-0.6002770546184063
		>50K		<=50K

Error sum for iteration 12200 = 56.509867335237566

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6498337212298757	-0.64282066699793	age
Hidden Weights:
	-0.8345579667924972	1.0170910267471482
	0.33520022269260147	-0.6002691168431273
		>50K		<=50K

Error sum for iteration 12300 = 56.50986705359408

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6502741936592137	-0.6429553203167948	age
Hidden Weights:
	-0.8345514080182314	1.0170844669494297
	0.33519230445092596	-0.6002611985584759
		>50K		<=50K

Error sum for iteration 12400 = 56.5098667763036

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6507111323556327	-0.643089639167492	age
Hidden Weights:
	-0.83454490146654	1.0170779593881794
	0.33518440560304524	-0.6002532996679346
		>50K		<=50K

Error sum for iteration 12500 = 56.50986650326336

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6511445937877424	-0.6432236252142038	age
Hidden Weights:
	-0.8345384463062612	1.0170715032319548
	0.3351765260531696	-0.6002454200756528
		>50K		<=50K

Error sum for iteration 12600 = 56.5098662343738

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6515746330793378	-0.6433572801086846	age
Hidden Weights:
	-0.8345320417259753	1.0170650976690399
	0.335168665706231	-0.6002375596866538
		>50K		<=50K

Error sum for iteration 12700 = 56.50986596953873

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6520013040518516	-0.6434906054903857	age
Hidden Weights:
	-0.8345256869333788	1.017058741906806
	0.3351608244678709	-0.6002297184065246
		>50K		<=50K

Error sum for iteration 12800 = 56.50986570866478

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6524246592650935	-0.6436236029865595	age
Hidden Weights:
	-0.8345193811546935	1.017052435171205
	0.3351530022443983	-0.6002218961415615
		>50K		<=50K

Error sum for iteration 12900 = 56.50986545166092

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6528447500563762	-0.6437562742124799	age
Hidden Weights:
	-0.8345131236340912	1.017046176706147
	0.33514519894278644	-0.6002140927987935
		>50K		<=50K

Error sum for iteration 13000 = 56.50986519844003

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6532616265781447	-0.6438886207714812	age
Hidden Weights:
	-0.8345069136331402	1.017039965772897
	0.33513741447076517	-0.6002063082858976
		>50K		<=50K

Error sum for iteration 13100 = 56.509864948916594

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6536753378342121	-0.644020644255013	age
Hidden Weights:
	-0.8345007504302768	1.0170338016496394
	0.3351296487366842	-0.600198542511302
		>50K		<=50K

Error sum for iteration 13200 = 56.509864703008034

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6540859317146505	-0.6441523462429594	age
Hidden Weights:
	-0.8344946333202765	1.0170276836309287
	0.33512190164960287	-0.6001907953839928
		>50K		<=50K

Error sum for iteration 13300 = 56.509864460634475

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6544934550292534	-0.644283728303544	age
Hidden Weights:
	-0.8344885616137999	1.0170216110271533
	0.33511417311923064	-0.6001830668136766
		>50K		<=50K

Error sum for iteration 13400 = 56.50986422171805

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6548979535398123	-0.64441479199351	age
Hidden Weights:
	-0.8344825346368929	1.0170155831641297
	0.3351064630559224	-0.6001753567107269
		>50K		<=50K

Error sum for iteration 13500 = 56.50986398618327

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6552994719912019	-0.6445455388582979	age
Hidden Weights:
	-0.8344765517305354	1.0170095993825885
	0.33509877137069644	-0.6001676649861272
		>50K		<=50K

Error sum for iteration 13600 = 56.509863753957

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.655698054141276	-0.644675970432053	age
Hidden Weights:
	-0.8344706122502041	1.0170036590377902
	0.33509109797523356	-0.600159991551492
		>50K		<=50K

Error sum for iteration 13700 = 56.50986352496799

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6560937427898194	-0.6448060882377936	age
Hidden Weights:
	-0.8344647155654401	1.016997761499084
	0.33508344278180197	-0.6001523363191492
		>50K		<=50K

Error sum for iteration 13800 = 56.50986329914737

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6564865798062406	-0.6449358937875532	age
Hidden Weights:
	-0.8344588610594776	1.0169919061494639
	0.3350758057033412	-0.60014469920203
		>50K		<=50K

Error sum for iteration 13900 = 56.50986307642785

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.656876606156364	-0.645065388582396	age
Hidden Weights:
	-0.8344530481288049	1.0169860923852185
	0.3350681866534211	-0.6001370801137246
		>50K		<=50K

Error sum for iteration 14000 = 56.509862856744206

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6572638619282354	-0.645194574112579	age
Hidden Weights:
	-0.8344472761828096	1.016980319615548
	0.33506058554617507	-0.6001294789683657
		>50K		<=50K

Error sum for iteration 14100 = 56.50986264003332

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6576483863572076	-0.6453234518576704	age
Hidden Weights:
	-0.8344415446434162	1.0169745872621523
	0.3350530022964152	-0.6001218956808041
		>50K		<=50K

Error sum for iteration 14200 = 56.50986242623318

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.658030217849771	-0.6454520232866363	age
Hidden Weights:
	-0.8344358529447123	1.0169688947589623
	0.3350454368195231	-0.6001143301662981
		>50K		<=50K

Error sum for iteration 14300 = 56.5098622152842

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6584093940068646	-0.6455802898578832	age
Hidden Weights:
	-0.834430200532639	1.0169632415517071
	0.33503788903150805	-0.6001067823409211
		>50K		<=50K

Error sum for iteration 14400 = 56.50986200712815

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6587859516461869	-0.6457082530194134	age
Hidden Weights:
	-0.8344245868646394	1.0169576270976506
	0.335030358848949	-0.6000992521213059
		>50K		<=50K

Error sum for iteration 14500 = 56.509861801708205

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6591599268239258	-0.6458359142089718	age
Hidden Weights:
	-0.8344190114093382	1.0169520508652778
	0.3350228461890635	-0.6000917394245517
		>50K		<=50K

Error sum for iteration 14600 = 56.50986159896925

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6595313548555833	-0.645963274854048	age
Hidden Weights:
	-0.8344134736462728	1.0169465123339299
	0.3350153509695707	-0.6000842441684766
		>50K		<=50K

Error sum for iteration 14700 = 56.509861398857765

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6599002703360629	-0.646090336372003	age
Hidden Weights:
	-0.8344079730655402	1.0169410109935453
	0.33500787310886054	-0.6000767662714046
		>50K		<=50K

Error sum for iteration 14800 = 56.509861201321435

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.660266707159302	-0.6462171001702145	age
Hidden Weights:
	-0.8344025091675706	1.0169355463443652
	0.33500041252582047	-0.6000693056522992
		>50K		<=50K

Error sum for iteration 14900 = 56.50986100630957

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6606306985370032	-0.6463435676461864	age
Hidden Weights:
	-0.8343970814628053	1.016930117896709
	0.3349929691399768	-0.600061862230613
		>50K		<=50K

Error sum for iteration 15000 = 56.509860813772505

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6609922770167767	-0.6464697401874838	age
Hidden Weights:
	-0.8343916894714403	1.0169247251706124
	0.3349855428713924	-0.6000544359263774
		>50K		<=50K

Error sum for iteration 15100 = 56.509860623662405

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6613514744998827	-0.6465956191719974	age
Hidden Weights:
	-0.8343863327231996	1.0169193676956312
	0.334978133640687	-0.6000470266602217
		>50K		<=50K

Error sum for iteration 15200 = 56.50986043593201

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6617083222581794	-0.6467212059679449	age
Hidden Weights:
	-0.8343810107570478	1.016914045010607
	0.33497074136900495	-0.6000396343533446
		>50K		<=50K

Error sum for iteration 15300 = 56.509860250535894

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6620628509505513	-0.6468465019339785	age
Hidden Weights:
	-0.8343757231209461	1.0169087566633432
	0.3349633659780562	-0.600032258927436
		>50K		<=50K

Error sum for iteration 15400 = 56.50986006742939

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6624150906389078	-0.6469715084193307	age
Hidden Weights:
	-0.8343704693716489	1.016903502210463
	0.33495600739012005	-0.6000249003048055
		>50K		<=50K

Error sum for iteration 15500 = 56.50985988656899

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6627650708035534	-0.6470962267637379	age
Hidden Weights:
	-0.8343652490744761	1.0168982812171738
	0.3349486655279916	-0.6000175584081593
		>50K		<=50K

Error sum for iteration 15600 = 56.509859707912796

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6631128203580726	-0.647220658297763	age
Hidden Weights:
	-0.8343600618030553	1.016893093256936
	0.3349413403150043	-0.6000102331608521
		>50K		<=50K

Error sum for iteration 15700 = 56.5098595314191

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6634583676638253	-0.6473448043427064	age
Hidden Weights:
	-0.834354907139156	1.0168879379114126
	0.3349340316749885	-0.600002924486753
		>50K		<=50K

Error sum for iteration 15800 = 56.50985935704802

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6638017405439073	-0.6474686662107354	age
Hidden Weights:
	-0.8343497846724447	1.0168828147701323
	0.3349267395323534	-0.5999956323101968
		>50K		<=50K

Error sum for iteration 15900 = 56.50985918476048

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.664142966296747	-0.6475922452050306	age
Hidden Weights:
	-0.8343446940003149	1.0168777234303674
	0.3349194638119952	-0.5999883565561092
		>50K		<=50K

Error sum for iteration 16000 = 56.50985901451802

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6644820717090935	-0.6477155426196842	age
Hidden Weights:
	-0.8343396347276878	1.0168726634969227
	0.3349122044393199	-0.5999810971499427
		>50K		<=50K

Error sum for iteration 16100 = 56.50985884628342

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6648190830689074	-0.6478385597400761	age
Hidden Weights:
	-0.8343346064668274	1.016867634581935
	0.33490496134024295	-0.5999738540176065
		>50K		<=50K

Error sum for iteration 16200 = 56.50985868002037

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6651540261776039	-0.6479612978427259	age
Hidden Weights:
	-0.8343296088371238	1.0168626363047204
	0.33489773444121773	-0.5999666270854885
		>50K		<=50K

Error sum for iteration 16300 = 56.509858515693274

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6654869263619413	-0.6480837581953602	age
Hidden Weights:
	-0.834324641464994	1.0168576682915296
	0.33489052366916083	-0.5999594162805223
		>50K		<=50K

Error sum for iteration 16400 = 56.509858353267646

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6658178084856586	-0.6482059420572092	age
Hidden Weights:
	-0.8343197039836368	1.0168527301754937
	0.33488332895146405	-0.5999522215301357
		>50K		<=50K

Error sum for iteration 16500 = 56.50985819270974

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6661466969606753	-0.6483278506788759	age
Hidden Weights:
	-0.8343147960329086	1.016847821596359
	0.33487615021610134	-0.599945042762175
		>50K		<=50K

Error sum for iteration 16600 = 56.50985803398633

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6664736157580036	-0.6484494853024863	age
Hidden Weights:
	-0.8343099172591482	1.0168429422003484
	0.33486898739142074	-0.5999378799051295
		>50K		<=50K

Error sum for iteration 16700 = 56.50985787706534

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.666798588418283	-0.6485708471617418	age
Hidden Weights:
	-0.8343050673150209	1.0168380916400466
	0.33486184040630423	-0.5999307328878632
		>50K		<=50K

Error sum for iteration 16800 = 56.5098577219155

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6671216380620844	-0.6486919374820412	age
Hidden Weights:
	-0.8343002458593946	1.0168332695741993
	0.3348547091901168	-0.5999236016396968
		>50K		<=50K

Error sum for iteration 16900 = 56.50985756850571

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6674427873998031	-0.6488127574805798	age
Hidden Weights:
	-0.8342954525571491	1.0168284756675927
	0.33484759367268013	-0.5999164860904991
		>50K		<=50K

Error sum for iteration 17000 = 56.509857416806256

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6677620587412865	-0.6489333083662453	age
Hidden Weights:
	-0.8342906870790764	1.0168237095909451
	0.33484049378431924	-0.5999093861705351
		>50K		<=50K

Error sum for iteration 17100 = 56.50985726678774

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6680794740052901	-0.6490535913399129	age
Hidden Weights:
	-0.8342859491017148	1.0168189710206692
	0.3348334094558124	-0.5999023018105459
		>50K		<=50K

Error sum for iteration 17200 = 56.50985711842155

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6683950547284897	-0.6491736075944328	age
Hidden Weights:
	-0.8342812383072254	1.0168142596388632
	0.3348263406183414	-0.599895232941817
		>50K		<=50K

Error sum for iteration 17300 = 56.509856971679774

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6687088220743946	-0.6492933583146389	age
Hidden Weights:
	-0.8342765543832692	1.0168095751330863
	0.33481928720361676	-0.5998881794960056
		>50K		<=50K

Error sum for iteration 17400 = 56.50985682653496

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6690207968418209	-0.6494128446775757	age
Hidden Weights:
	-0.834271897022858	1.0168049171962732
	0.3348122491437555	-0.5998811414052393
		>50K		<=50K

Error sum for iteration 17500 = 56.50985668296034

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6693309994733274	-0.6495320678523463	age
Hidden Weights:
	-0.8342672659242647	1.0168002855266285
	0.33480522637132554	-0.5998741186021166
		>50K		<=50K

Error sum for iteration 17600 = 56.509856540930194

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6696394500633127	-0.6496510290003874	age
Hidden Weights:
	-0.8342626607908851	1.0167956798274487
	0.3347982188193966	-0.5998671110196896
		>50K		<=50K

Error sum for iteration 17700 = 56.509856400418336

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6699461683657586	-0.6497697292754204	age
Hidden Weights:
	-0.8342580813311264	1.0167910998070486
	0.3347912264214383	-0.5998601185913391
		>50K		<=50K

Error sum for iteration 17800 = 56.509856261400316

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6702511738020257	-0.6498881698235224	age
Hidden Weights:
	-0.8342535272582747	1.0167865451786398
	0.33478424911132443	-0.599853141251061
		>50K		<=50K

Error sum for iteration 17900 = 56.50985612385136

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6705544854682246	-0.6500063517832656	age
Hidden Weights:
	-0.8342489982904335	1.0167820156602625
	0.3347772868234215	-0.5998461789331638
		>50K		<=50K

Error sum for iteration 18000 = 56.5098559877479

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6708561221424626	-0.6501242762857403	age
Hidden Weights:
	-0.8342444941503625	1.016777510974585
	0.33477033949250123	-0.5998392315723421
		>50K		<=50K

Error sum for iteration 18100 = 56.509855853066476

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6711561022918147	-0.6502419444546106	age
Hidden Weights:
	-0.8342400145654087	1.0167730308488905
	0.3347634070537246	-0.5998322991039214
		>50K		<=50K

Error sum for iteration 18200 = 56.509855719784085

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6714544440792487	-0.6503593574061668	age
Hidden Weights:
	-0.8342355592674139	1.0167685750149527
	0.33475648944273506	-0.5998253814634616
		>50K		<=50K

Error sum for iteration 18300 = 56.5098555878785

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.671751165370191	-0.6504765162494767	age
Hidden Weights:
	-0.8342311279925755	1.0167641432088934
	0.3347495865955909	-0.5998184785869768
		>50K		<=50K

Error sum for iteration 18400 = 56.50985545732777

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6720462837390395	-0.6505934220862472	age
Hidden Weights:
	-0.8342267204813885	1.0167597351711202
	0.33474269844869475	-0.5998115904109068
		>50K		<=50K

Error sum for iteration 18500 = 56.509855328110504

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.672339816475439	-0.6507100760111848	age
Hidden Weights:
	-0.8342223364785536	1.0167553506462867
	0.33473582493893755	-0.5998047168721696
		>50K		<=50K

Error sum for iteration 18600 = 56.50985520020584

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6726317805903583	-0.6508264791118356	age
Hidden Weights:
	-0.8342179757328448	1.0167509893831106
	0.3347289660036145	-0.5997978579079718
		>50K		<=50K

Error sum for iteration 18700 = 56.50985507359304

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6729221928221303	-0.6509426324686844	age
Hidden Weights:
	-0.8342136379970784	1.0167466511343115
	0.3347221215803534	-0.5997910134560067
		>50K		<=50K

Error sum for iteration 18800 = 56.50985494825223

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6732110696422949	-0.6510585371551944	age
Hidden Weights:
	-0.834209323027997	1.0167423356565914
	0.3347152916072398	-0.5997841834543302
		>50K		<=50K

Error sum for iteration 18900 = 56.50985482416372

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6734984272611079	-0.6511741942380647	age
Hidden Weights:
	-0.834205030586173	1.0167380427104467
	0.3347084760227118	-0.5997773678414189
		>50K		<=50K

Error sum for iteration 19000 = 56.50985470130811

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6737842816331027	-0.6512896047770054	age
Hidden Weights:
	-0.8342007604359624	1.0167337720601692
	0.3347016747656546	-0.5997705665561028
		>50K		<=50K

Error sum for iteration 19100 = 56.50985457966668

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6740686484624993	-0.651404769824955	age
Hidden Weights:
	-0.8341965123454018	1.0167295234737683
	0.33469488777532286	-0.5997637795376952
		>50K		<=50K

Error sum for iteration 19200 = 56.50985445922091

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6743515432082607	-0.6515196904280999	age
Hidden Weights:
	-0.8341922860861428	1.0167252967228044
	0.3346881149913559	-0.5997570067258472
		>50K		<=50K

Error sum for iteration 19300 = 56.50985433995269

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6746329810893557	-0.6516343676259961	age
Hidden Weights:
	-0.8341880814333756	1.0167210915824227
	0.33468135635377677	-0.5997502480605797
		>50K		<=50K

Error sum for iteration 19400 = 56.50985422184428

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.674912977089632	-0.6517488024514935	age
Hidden Weights:
	-0.8341838981657498	1.0167169078312133
	0.33467461180302943	-0.599743503482201
		>50K		<=50K

Error sum for iteration 19500 = 56.50985410487836

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6751915459626424	-0.6518629959309635	age
Hidden Weights:
	-0.8341797360653109	1.0167127452511628
	0.3346678812798661	-0.5997367729315327
		>50K		<=50K

Error sum for iteration 19600 = 56.509853989038014

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6754687022363272	-0.6519769490841626	age
Hidden Weights:
	-0.8341755949174207	1.0167086036275856
	0.3346611647254261	-0.5997300563497784
		>50K		<=50K

Error sum for iteration 19700 = 56.50985387430629

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.675744460217537	-0.6520906629244322	age
Hidden Weights:
	-0.8341714745107103	1.0167044827490554
	0.3346544620812725	-0.599723353678417
		>50K		<=50K

Error sum for iteration 19800 = 56.509853760667184

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6760188339967094	-0.6522041384587789	age
Hidden Weights:
	-0.8341673746369875	1.0167003824073226
	0.3346477732892583	-0.5997166648594051
		>50K		<=50K

Error sum for iteration 19900 = 56.5098536481043

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6762918374519503	-0.6523173766877642	age
Hidden Weights:
	-0.8341632950912036	1.0166963023972833
	0.3346410982916838	-0.5997099898349391
		>50K		<=50K

Error sum for iteration 20000 = 56.50985353660219

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6765634842534262	-0.6524303786056651	age
Hidden Weights:
	-0.8341592356713621	1.0166922425169052
	0.3346344370311774	-0.5997033285476744
		>50K		<=50K

Error sum for iteration 20100 = 56.509853426145455

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6768337878675249	-0.652543145200533	age
Hidden Weights:
	-0.8341551961784671	1.016688202567125
	0.3346277894506982	-0.5996966809405888
		>50K		<=50K

Error sum for iteration 20200 = 56.509853316718896

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6771027615608348	-0.6526556774542247	age
Hidden Weights:
	-0.8341511764164727	1.016684182351891
	0.33462115549357085	-0.5996900469569397
		>50K		<=50K

Error sum for iteration 20300 = 56.50985320830787

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6773704184040675	-0.6527679763424333	age
Hidden Weights:
	-0.8341471761922226	1.0166801816779618
	0.3346145351034702	-0.5996834265404827
		>50K		<=50K

Error sum for iteration 20400 = 56.50985310089765

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6776367712758911	-0.6528800428348109	age
Hidden Weights:
	-0.8341431953153982	1.016676200354962
	0.3346079282244696	-0.5996768196352289
		>50K		<=50K

Error sum for iteration 20500 = 56.50985299447423

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6779018328667793	-0.6529918778949334	age
Hidden Weights:
	-0.8341392335984377	1.0166722381953015
	0.33460133480092813	-0.599670226185632
		>50K		<=50K

Error sum for iteration 20600 = 56.50985288902333

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6781656156825604	-0.6531034824803797	age
Hidden Weights:
	-0.8341352908565045	1.0166682950141048
	0.3345947547775988	-0.5996636461363469
		>50K		<=50K

Error sum for iteration 20700 = 56.509852784531574

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6784281320480059	-0.6532148575428073	age
Hidden Weights:
	-0.8341313669074301	1.0166643706291627
	0.334588188099534	-0.5996570794324564
		>50K		<=50K

Error sum for iteration 20800 = 56.50985268098525

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6786893941103	-0.6533260040279862	age
Hidden Weights:
	-0.8341274615716824	1.0166604648608704
	0.33458163471213326	-0.5996505260193614
		>50K		<=50K

Error sum for iteration 20900 = 56.509852578371486

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6789494138424204	-0.6534369228757949	age
Hidden Weights:
	-0.8341235746722614	1.0166565775322058
	0.33457509456116913	-0.5996439858428458
		>50K		<=50K

Error sum for iteration 21000 = 56.50985247667715

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6792082030466163	-0.6535476150203837	age
Hidden Weights:
	-0.8341197060347215	1.0166527084686858
	0.33456856759269155	-0.5996374588489644
		>50K		<=50K

Error sum for iteration 21100 = 56.50985237588957

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6794657733574311	-0.6536580813901742	age
Hidden Weights:
	-0.8341158554870687	1.0166488574982546
	0.3345620537531224	-0.5996309449841337
		>50K		<=50K

Error sum for iteration 21200 = 56.509852275996245

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6797221362449513	-0.6537683229077919	age
Hidden Weights:
	-0.8341120228597322	1.0166450244513179
	0.3345555529891723	-0.5996244441950298
		>50K		<=50K

Error sum for iteration 21300 = 56.50985217698507

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6799773030179563	-0.6538783404902511	age
Hidden Weights:
	-0.8341082079855342	1.0166412091606574
	0.33454906524793204	-0.5996179564287779
		>50K		<=50K

Error sum for iteration 21400 = 56.5098520788439

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6802312848267528	-0.6539881350489621	age
Hidden Weights:
	-0.8341044106996185	1.0166374114613796
	0.3345425904767401	-0.5996114816327163
		>50K		<=50K

Error sum for iteration 21500 = 56.509851981561

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6804840926663314	-0.6540977074898529	age
Hidden Weights:
	-0.8341006308394229	1.0166336311908841
	0.3345361286233475	-0.5996050197545828
		>50K		<=50K

Error sum for iteration 21600 = 56.5098518851249

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6807357373791532	-0.6542070587131775	age
Hidden Weights:
	-0.8340968682446428	1.0166298681888128
	0.33452967963574254	-0.5995985707423481
		>50K		<=50K

Error sum for iteration 21700 = 56.50985178952413

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6809862296579581	-0.6543161896138621	age
Hidden Weights:
	-0.8340931227571775	1.0166261222970598
	0.33452324346224277	-0.5995921345443653
		>50K		<=50K

Error sum for iteration 21800 = 56.50985169474751

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6812355800485007	-0.654425101081337	age
Hidden Weights:
	-0.8340893942210839	1.0166223933596155
	0.3345168200515137	-0.5995857111093016
		>50K		<=50K

Error sum for iteration 21900 = 56.509851600784245

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6814837989522	-0.6545337939997125	age
Hidden Weights:
	-0.8340856824825577	1.0166186812226417
	0.33451040935253606	-0.5995793003860449
		>50K		<=50K

Error sum for iteration 22000 = 56.509851507623296

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6817308966288492	-0.6546422692476617	age
Hidden Weights:
	-0.8340819873898841	1.0166149857343911
	0.33450401131453994	-0.5995729023239217
		>50K		<=50K

Error sum for iteration 22100 = 56.50985141525452

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6819768831991528	-0.654750527698585	age
Hidden Weights:
	-0.8340783087933824	1.0166113067451703
	0.33449762588708415	-0.599566516872417
		>50K		<=50K

Error sum for iteration 22200 = 56.509851323667284

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6822217686471669	-0.6548585702206549	age
Hidden Weights:
	-0.83407464654541	1.0166076441072858
	0.3344912530200292	-0.5995601439814361
		>50K		<=50K

Error sum for iteration 22300 = 56.509851232851226

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6824655628228163	-0.6549663976768452	age
Hidden Weights:
	-0.8340710005002996	1.0166039976750456
	0.3344848926635809	-0.5995537836011094
		>50K		<=50K

Error sum for iteration 22400 = 56.50985114279657

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6827082754442422	-0.6550740109249806	age
Hidden Weights:
	-0.8340673705143071	1.0166003673046538
	0.3344785447681875	-0.5995474356818882
		>50K		<=50K

Error sum for iteration 22500 = 56.50985105349354

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6829499161002115	-0.655181410817642	age
Hidden Weights:
	-0.8340637564456153	1.0165967528542732
	0.3344722092845651	-0.599541100174581
		>50K		<=50K

Error sum for iteration 22600 = 56.50985096493231

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6831904942523527	-0.6552885982023963	age
Hidden Weights:
	-0.834060158154287	1.0165931541839273
	0.334465886163788	-0.5995347770302546
		>50K		<=50K

Error sum for iteration 22700 = 56.50985087710335

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6834300192374041	-0.6553955739218167	age
Hidden Weights:
	-0.8340565755022074	1.016589571155471
	0.3344595753572033	-0.5995284662002377
		>50K		<=50K

Error sum for iteration 22800 = 56.509850789997344

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6836685002693769	-0.6555023388133985	age
Hidden Weights:
	-0.8340530083530937	1.0165860036326133
	0.3344532768164495	-0.599522167636127
		>50K		<=50K

Error sum for iteration 22900 = 56.509850703605345

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6839059464417577	-0.6556088937097173	age
Hidden Weights:
	-0.8340494565724176	1.0165824514807664
	0.33444699049342397	-0.5995158812898693
		>50K		<=50K

Error sum for iteration 23000 = 56.50985061791807

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6841423667295744	-0.655715239438338	age
Hidden Weights:
	-0.8340459200274208	1.0165789145671602
	0.33444071634030587	-0.599509607113644
		>50K		<=50K

Error sum for iteration 23100 = 56.50985053292682

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6843777699914398	-0.6558213768219937	age
Hidden Weights:
	-0.8340423985870453	1.0165753927606973
	0.3344344543095763	-0.5995033450599526
		>50K		<=50K

Error sum for iteration 23200 = 56.509850448622636

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6846121649715674	-0.6559273066785429	age
Hidden Weights:
	-0.8340388921219285	1.0165718859319999
	0.3344282043539918	-0.5994970950814851
		>50K		<=50K

Error sum for iteration 23300 = 56.50985036499725

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6848455603016825	-0.6560330298210694	age
Hidden Weights:
	-0.8340354005043625	1.0165683939533343
	0.33442196642660127	-0.5994908571313082
		>50K		<=50K

Error sum for iteration 23400 = 56.509850282042024

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6850779645030399	-0.6561385470578696	age
Hidden Weights:
	-0.8340319236082971	1.0165649166986124
	0.33441574048070133	-0.5994846311627516
		>50K		<=50K

Error sum for iteration 23500 = 56.50985019974871

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6853093859882664	-0.6562438591924868	age
Hidden Weights:
	-0.8340284613092416	1.0165614540433299
	0.3344095264698813	-0.5994784171293548
		>50K		<=50K

Error sum for iteration 23600 = 56.50985011810945

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.68553983306314	-0.6563489670237462	age
Hidden Weights:
	-0.8340250134843132	1.0165580058645394
	0.3344033243479872	-0.5994722149850159
		>50K		<=50K

Error sum for iteration 23700 = 56.50985003711574

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6857693139284788	-0.6564538713457926	age
Hidden Weights:
	-0.8340215800121674	1.0165545720408982
	0.33439713406913535	-0.5994660246838162
		>50K		<=50K

Error sum for iteration 23800 = 56.50984995676011

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6859978366818152	-0.6565585729482216	age
Hidden Weights:
	-0.8340181607729797	1.0165511524525312
	0.33439095558770787	-0.599459846180161
		>50K		<=50K

Error sum for iteration 23900 = 56.50984987703448

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6862254093192568	-0.6566630726159723	age
Hidden Weights:
	-0.8340147556484224	1.016547746981136
	0.3343847888583524	-0.5994536794287485
		>50K		<=50K

Error sum for iteration 24000 = 56.50984979793143

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6864520397370096	-0.6567673711294604	age
Hidden Weights:
	-0.8340113645216507	1.0165443555098033
	0.3343786338359758	-0.5994475243844176
		>50K		<=50K

Error sum for iteration 24100 = 56.50984971944365

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.686677735733155	-0.656871469264532	age
Hidden Weights:
	-0.8340079872772621	1.0165409779231178
	0.33437249047574946	-0.5994413810023073
		>50K		<=50K

Error sum for iteration 24200 = 56.50984964156335

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6869025050092307	-0.6569753677926189	age
Hidden Weights:
	-0.8340046238012844	1.0165376141070581
	0.33436635873310067	-0.5994352492378494
		>50K		<=50K

Error sum for iteration 24300 = 56.50984956428363

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6871263551718491	-0.657079067480641	age
Hidden Weights:
	-0.8340012739811404	1.016534263949046
	0.3343602385637373	-0.5994291290467739
		>50K		<=50K

Error sum for iteration 24400 = 56.50984948759716

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.687349293734214	-0.657182569091096	age
Hidden Weights:
	-0.8339979377056365	1.0165309273378536
	0.3343541299235819	-0.5994230203849893
		>50K		<=50K

Error sum for iteration 24500 = 56.509849411496816

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6875713281175944	-0.657285873382151	age
Hidden Weights:
	-0.8339946148649239	1.01652760416363
	0.33434803276881525	-0.5994169232087181
		>50K		<=50K

Error sum for iteration 24600 = 56.50984933597584

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6877924656529557	-0.6573889811075523	age
Hidden Weights:
	-0.8339913053505139	1.016524294317837
	0.3343419470558933	-0.5994108374744302
		>50K		<=50K

Error sum for iteration 24700 = 56.50984926102752

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6880127135823149	-0.6574918930168309	age
Hidden Weights:
	-0.8339880090551947	1.0165209976932732
	0.33433587274149135	-0.599404763138752
		>50K		<=50K

Error sum for iteration 24800 = 56.509849186645134

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6882320790601909	-0.6575946098551201	age
Hidden Weights:
	-0.8339847258730747	1.016517714183982
	0.33432980978254534	-0.5993987001586367
		>50K		<=50K

Error sum for iteration 24900 = 56.5098491128218

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6884505691550803	-0.6576971323633477	age
Hidden Weights:
	-0.8339814556995224	1.0165144436853448
	0.33432375813625886	-0.5993926484912416
		>50K		<=50K

Error sum for iteration 25000 = 56.50984903955139

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6886681908506824	-0.6577994612782416	age
Hidden Weights:
	-0.833978198431147	1.0165111860939295
	0.33431771776005736	-0.5993866080939904
		>50K		<=50K

Error sum for iteration 25100 = 56.50984896682735

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6888849510474515	-0.6579015973323109	age
Hidden Weights:
	-0.8339749539658028	1.0165079413075897
	0.33431168861157257	-0.5993805789245652
		>50K		<=50K

Error sum for iteration 25200 = 56.50984889464333

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6891008565636829	-0.6580035412539668	age
Hidden Weights:
	-0.8339717222025574	1.0165047092253543
	0.3343056706487327	-0.5993745609408521
		>50K		<=50K

Error sum for iteration 25300 = 56.5098488229935

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6893159141370961	-0.6581052937674208	age
Hidden Weights:
	-0.8339685030416595	1.0165014897474411
	0.3342996638296631	-0.5993685541010025
		>50K		<=50K

Error sum for iteration 25400 = 56.50984875187122

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.68953013042583	-0.6582068555928638	age
Hidden Weights:
	-0.8339652963845423	1.0164982827752835
	0.33429366811272787	-0.5993625583634116
		>50K		<=50K

Error sum for iteration 25500 = 56.50984868127087

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6897435120098087	-0.6583082274463296	age
Hidden Weights:
	-0.8339621021337746	1.0164950882114254
	0.33428768345656196	-0.5993565736866453
		>50K		<=50K

Error sum for iteration 25600 = 56.50984861118661

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6899560653919933	-0.6584094100399289	age
Hidden Weights:
	-0.8339589201930813	1.0164919059595676
	0.33428170981999006	-0.5993506000295629
		>50K		<=50K

Error sum for iteration 25700 = 56.50984854161228

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6901677969995429	-0.6585104040816854	age
Hidden Weights:
	-0.8339557504673001	1.0164887359245312
	0.33427574716209196	-0.5993446373512693
		>50K		<=50K

Error sum for iteration 25800 = 56.50984847254234

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6903787131849821	-0.6586112102756875	age
Hidden Weights:
	-0.8339525928623773	1.0164855780122377
	0.334269795442171	-0.5993386856110242
		>50K		<=50K

Error sum for iteration 25900 = 56.50984840397138

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6905888202273428	-0.6587118293220517	age
Hidden Weights:
	-0.8339494472853286	1.0164824321296781
	0.3342638546197223	-0.5993327447683636
		>50K		<=50K

Error sum for iteration 26000 = 56.50984833589343

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6907981243333761	-0.6588122619170322	age
Hidden Weights:
	-0.833946313644243	1.0164792981849535
	0.3342579246545052	-0.5993268147830378
		>50K		<=50K

Error sum for iteration 26100 = 56.50984826830332

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6910066316384671	-0.6589125087529832	age
Hidden Weights:
	-0.833943191848275	1.0164761760871743
	0.33425200550649775	-0.5993208956149999
		>50K		<=50K

Error sum for iteration 26200 = 56.50984820119542

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6912143482079547	-0.6590125705183383	age
Hidden Weights:
	-0.8339400818076028	1.0164730657465177
	0.3342460971358999	-0.5993149872244382
		>50K		<=50K

Error sum for iteration 26300 = 56.509848134564635

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6914212800381019	-0.6591124478978145	age
Hidden Weights:
	-0.8339369834334225	1.0164699670741395
	0.33424019950313233	-0.5993090895717997
		>50K		<=50K

Error sum for iteration 26400 = 56.50984806840563

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6916274330570934	-0.6592121415722729	age
Hidden Weights:
	-0.833933896637949	1.0164668799822416
	0.3342343125688136	-0.5993032026176839
		>50K		<=50K

Error sum for iteration 26500 = 56.509848002713206

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6918328131260902	-0.6593116522187441	age
Hidden Weights:
	-0.8339308213343802	1.0164638043840077
	0.3342284362938016	-0.5992973263230171
		>50K		<=50K

Error sum for iteration 26600 = 56.50984793748246

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6920374260402863	-0.6594109805106576	age
Hidden Weights:
	-0.8339277574368757	1.0164607401935861
	0.33422257063918	-0.5992914606487932
		>50K		<=50K

Error sum for iteration 26700 = 56.50984787270833

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6922412775298336	-0.6595101271176494	age
Hidden Weights:
	-0.8339247048605706	1.0164576873260898
	0.33421671556622207	-0.5992856055563087
		>50K		<=50K

Error sum for iteration 26800 = 56.50984780838573

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6924443732608021	-0.6596090927056262	age
Hidden Weights:
	-0.8339216635215483	1.0164546456975938
	0.3342108710364425	-0.5992797610070278
		>50K		<=50K

Error sum for iteration 26900 = 56.50984774451001

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6926467188362198	-0.6597078779368818	age
Hidden Weights:
	-0.8339186333368069	1.016451615225069
	0.334205037011514	-0.5992739269627083
		>50K		<=50K

Error sum for iteration 27000 = 56.50984768107621

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6928483197969713	-0.6598064834701162	age
Hidden Weights:
	-0.8339156142242848	1.016448595826445
	0.3341992134533226	-0.5992681033852577
		>50K		<=50K

Error sum for iteration 27100 = 56.50984761807975

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6930491816226634	-0.6599049099603731	age
Hidden Weights:
	-0.8339126061028099	1.0164455874205214
	0.33419340032403266	-0.5992622902368129
		>50K		<=50K

Error sum for iteration 27200 = 56.50984755551581

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6932493097325458	-0.660003158059125	age
Hidden Weights:
	-0.8339096088921062	1.016442589927022
	0.33418759758594946	-0.5992564874796581
		>50K		<=50K

Error sum for iteration 27300 = 56.509847493380086

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6934487094864289	-0.6601012284142483	age
Hidden Weights:
	-0.8339066225127894	1.0164396032665264
	0.33418180520161533	-0.5992506950762628
		>50K		<=50K

Error sum for iteration 27400 = 56.50984743166786

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6936473861854715	-0.6601991216702081	age
Hidden Weights:
	-0.8339036468863056	1.0164366273605019
	0.3341760231337658	-0.5992449129894597
		>50K		<=50K

Error sum for iteration 27500 = 56.509847370374644

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6938453450731835	-0.6602968384678156	age
Hidden Weights:
	-0.8339006819349906	1.0164336621312362
	0.33417025134535033	-0.5992391411821315
		>50K		<=50K

Error sum for iteration 27600 = 56.509847309496145

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6940425913361085	-0.6603943794445172	age
Hidden Weights:
	-0.8338977275820028	1.0164307075018715
	0.3341644897994792	-0.5992333796174255
		>50K		<=50K

Error sum for iteration 27700 = 56.509847249027985

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6942391301047238	-0.6604917452342397	age
Hidden Weights:
	-0.8338947837513333	1.0164277633964163
	0.33415873845947985	-0.5992276282586774
		>50K		<=50K

Error sum for iteration 27800 = 56.509847188966056

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6944349664542212	-0.6605889364675709	age
Hidden Weights:
	-0.8338918503677912	1.0164248297396332
	0.33415299728889436	-0.5992218870694356
		>50K		<=50K

Error sum for iteration 27900 = 56.50984712930593

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6946301054052882	-0.6606859537715639	age
Hidden Weights:
	-0.8338889273569816	1.0164219064571223
	0.3341472662514552	-0.5992161560134126
		>50K		<=50K

Error sum for iteration 28000 = 56.50984707004356

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6948245519249512	-0.6607827977699909	age
Hidden Weights:
	-0.8338860146453233	1.016418993475284
	0.33414154531107204	-0.5992104350545404
		>50K		<=50K

Error sum for iteration 28100 = 56.509847011174806

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6950183109271919	-0.6608794690832659	age
Hidden Weights:
	-0.8338831121599946	1.0164160907212905
	0.3341358344318775	-0.5992047241569312
		>50K		<=50K

Error sum for iteration 28200 = 56.50984695269565

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6952113872738976	-0.6609759683284284	age
Hidden Weights:
	-0.8338802198289592	1.016413198123079
	0.33413013357815197	-0.5991990232848721
		>50K		<=50K

Error sum for iteration 28300 = 56.50984689460234

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6954037857754709	-0.6610722961192309	age
Hidden Weights:
	-0.8338773375809497	1.016410315609375
	0.33412444271440284	-0.5991933324028663
		>50K		<=50K

Error sum for iteration 28400 = 56.5098468368905

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6955955111915486	-0.661168453066118	age
Hidden Weights:
	-0.8338744653454178	1.0164074431096302
	0.33411876180533207	-0.599187651475563
		>50K		<=50K

Error sum for iteration 28500 = 56.50984677955678

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6957865682318096	-0.6612644397763697	age
Hidden Weights:
	-0.8338716030525826	1.0164045805540336
	0.33411309081578777	-0.5991819804678852
		>50K		<=50K

Error sum for iteration 28600 = 56.50984672259692

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6959769615565937	-0.6613602568539636	age
Hidden Weights:
	-0.8338687506333767	1.016401727873501
	0.33410742971086244	-0.5991763193448527
		>50K		<=50K

Error sum for iteration 28700 = 56.50984666600743

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6961666957774882	-0.6614559048996129	age
Hidden Weights:
	-0.8338659080194526	1.0163988849996912
	0.3341017784557782	-0.5991706680717338
		>50K		<=50K

Error sum for iteration 28800 = 56.50984660978447

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6963557754582625	-0.6615513845109081	age
Hidden Weights:
	-0.8338630751431911	1.016396051864969
	0.33409613701595287	-0.5991650266139803
		>50K		<=50K

Error sum for iteration 28900 = 56.509846553924405

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6965442051153095	-0.66164669628226	age
Hidden Weights:
	-0.8338602519376495	1.016393228402376
	0.33409050535701246	-0.599159394937146
		>50K		<=50K

Error sum for iteration 29000 = 56.509846498423784

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6967319892184526	-0.6617418408049616	age
Hidden Weights:
	-0.8338574383365899	1.0163904145456442
	0.33408488344473936	-0.5991537730071358
		>50K		<=50K

Error sum for iteration 29100 = 56.50984644327869

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6969191321914155	-0.6618368186671019	age
Hidden Weights:
	-0.8338546342744451	1.0163876102292233
	0.3340792712451126	-0.5991481607898101
		>50K		<=50K

Error sum for iteration 29200 = 56.509846388485855

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6971056384125672	-0.6619316304537417	age
Hidden Weights:
	-0.8338518396863175	1.0163848153881625
	0.3340736687242867	-0.5991425582513648
		>50K		<=50K

Error sum for iteration 29300 = 56.50984633404188

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6972915122155644	-0.6620262767468453	age
Hidden Weights:
	-0.8338490545079776	1.0163820299582575
	0.3340680758485768	-0.599136965358117
		>50K		<=50K

Error sum for iteration 29400 = 56.50984627994317

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.697476757889904	-0.662120758125318	age
Hidden Weights:
	-0.8338462786758364	1.0163792538759036
	0.3340624925844935	-0.5991313820765402
		>50K		<=50K

Error sum for iteration 29500 = 56.509846226186454

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6976613796815122	-0.6622150751649724	age
Hidden Weights:
	-0.8338435121269716	1.0163764870781475
	0.33405691889871786	-0.5991258083732842
		>50K		<=50K

Error sum for iteration 29600 = 56.50984617276836

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6978453817933322	-0.6623092284386548	age
Hidden Weights:
	-0.8338407547990698	1.0163737295026942
	0.3340513547580967	-0.5991202442153094
		>50K		<=50K

Error sum for iteration 29700 = 56.50984611968544

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6980287683859457	-0.6624032185162453	age
Hidden Weights:
	-0.833838006630464	1.0163709810878505
	0.3340458001296531	-0.5991146895695253
		>50K		<=50K

Error sum for iteration 29800 = 56.509846066934784

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6982115435781301	-0.6624970459646717	age
Hidden Weights:
	-0.8338352675600958	1.0163682417725342
	0.33404025498056705	-0.5991091444031683
		>50K		<=50K

Error sum for iteration 29900 = 56.509846014512966

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6983937114473873	-0.6625907113478343	age
Hidden Weights:
	-0.8338325375275172	1.0163655114963077
	0.33403471927822936	-0.5991036086836075
		>50K		<=50K

Error sum for iteration 30000 = 56.509845962416684

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6985752760305795	-0.6626842152267076	age
Hidden Weights:
	-0.8338298164728882	1.016362790199289
	0.3340291929901506	-0.5990980823783861
		>50K		<=50K

Error sum for iteration 30100 = 56.50984591064325

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6987562413242712	-0.6627775581593236	age
Hidden Weights:
	-0.8338271043369551	1.0163600778222381
	0.3340236760840414	-0.5990925654552263
		>50K		<=50K

Error sum for iteration 30200 = 56.50984585918919

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6989366112854406	-0.6628707407009471	age
Hidden Weights:
	-0.8338244010610505	1.016357374306472
	0.33401816852778776	-0.5990870578820051
		>50K		<=50K

Error sum for iteration 30300 = 56.509845808051715

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6991163898320263	-0.6629637634039096	age
Hidden Weights:
	-0.8338217065870913	1.0163546795938934
	0.3340126702894036	-0.5990815596267267
		>50K		<=50K

Error sum for iteration 30400 = 56.50984575722767

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6992955808432658	-0.6630566268176397	age
Hidden Weights:
	-0.8338190208575701	1.0163519936269778
	0.33400718133708546	-0.5990760706575854
		>50K		<=50K

Error sum for iteration 30500 = 56.50984570671416

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.699474188160372	-0.6631493314887207	age
Hidden Weights:
	-0.8338163438155236	1.0163493163487767
	0.3340017016392207	-0.5990705909429048
		>50K		<=50K

Error sum for iteration 30600 = 56.50984565650817

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6996522155869405	-0.6632418779610324	age
Hidden Weights:
	-0.8338136754045627	1.016346647702878
	0.333996231164313	-0.5990651204512427
		>50K		<=50K

Error sum for iteration 30700 = 56.5098456066069

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.6998296668894471	-0.663334266775612	age
Hidden Weights:
	-0.8338110155688362	1.0163439876334073
	0.33399076988103893	-0.5990596591513023
		>50K		<=50K

Error sum for iteration 30800 = 56.509845557007566

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7000065457977295	-0.6634264984707033	age
Hidden Weights:
	-0.8338083642530384	1.0163413360850575
	0.33398531775823564	-0.5990542070119587
		>50K		<=50K

Error sum for iteration 30900 = 56.509845507707155

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7001828560055573	-0.663518573581795	age
Hidden Weights:
	-0.8338057214024086	1.0163386930030507
	0.3339798747649188	-0.5990487640021152
		>50K		<=50K

Error sum for iteration 31000 = 56.509845458703126

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7003586011709101	-0.6636104926416174	age
Hidden Weights:
	-0.8338030869627021	1.0163360583331351
	0.33397444087025613	-0.599043330090994
		>50K		<=50K

Error sum for iteration 31100 = 56.50984540999255

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7005337849165553	-0.663702256180284	age
Hidden Weights:
	-0.8338004608801751	1.0163334320215789
	0.3339690160435841	-0.5990379052478885
		>50K		<=50K

Error sum for iteration 31200 = 56.509845361572815

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7007084108305792	-0.6637938647250827	age
Hidden Weights:
	-0.8337978431016331	1.0163308140151677
	0.33396360025435695	-0.5990324894423059
		>50K		<=50K

Error sum for iteration 31300 = 56.509845313441126

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7008824824666289	-0.6638853188006493	age
Hidden Weights:
	-0.8337952335743841	1.0163282042611754
	0.33395819347219796	-0.5990270826438251
		>50K		<=50K

Error sum for iteration 31400 = 56.50984526559494

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7010560033445086	-0.6639766189290157	age
Hidden Weights:
	-0.8337926322462184	1.0163256027074246
	0.3339527956668716	-0.5990216848222542
		>50K		<=50K

Error sum for iteration 31500 = 56.5098452180317

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7012289769505577	-0.6640677656295436	age
Hidden Weights:
	-0.8337900390654376	1.016323009302153
	0.33394740680831986	-0.5990162959475177
		>50K		<=50K

Error sum for iteration 31600 = 56.50984517074879

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7014014067380648	-0.664158759418982	age
Hidden Weights:
	-0.8337874539808258	1.0163204239941808
	0.33394202686663116	-0.5990109159897692
		>50K		<=50K

Error sum for iteration 31700 = 56.50984512374351

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7015732961276798	-0.6642496008114099	age
Hidden Weights:
	-0.8337848769416526	1.0163178467327532
	0.33393665581204374	-0.5990055449191818
		>50K		<=50K

Error sum for iteration 31800 = 56.5098450770135

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7017446485078415	-0.6643402903183434	age
Hidden Weights:
	-0.8337823078976532	1.016315277467606
	0.33393129361494567	-0.599000182706092
		>50K		<=50K

Error sum for iteration 31900 = 56.50984503055637

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7019154672352411	-0.6644308284487136	age
Hidden Weights:
	-0.8337797467990524	1.0163127161489285
	0.33392594024587474	-0.5989948293210857
		>50K		<=50K

Error sum for iteration 32000 = 56.50984498436943

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7020857556350539	-0.6645212157089964	age
Hidden Weights:
	-0.8337771935965204	1.0163101627274032
	0.33392059567548943	-0.5989894847348243
		>50K		<=50K

Error sum for iteration 32100 = 56.50984493845032

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7022555170014684	-0.6646114526029758	age
Hidden Weights:
	-0.8337746482412056	1.016307617154182
	0.3339152598746291	-0.598984148918102
		>50K		<=50K

Error sum for iteration 32200 = 56.50984489279677

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7024247545980611	-0.6647015396319582	age
Hidden Weights:
	-0.8337721106846955	1.016305079380821
	0.33390993281426995	-0.5989788218419463
		>50K		<=50K

Error sum for iteration 32300 = 56.509844847406335

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.702593471658133	-0.6647914772947601	age
Hidden Weights:
	-0.8337695808790199	1.0163025493593567
	0.3339046144655046	-0.5989735034774848
		>50K		<=50K

Error sum for iteration 32400 = 56.509844802276675

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7027616713850975	-0.6648812660877575	age
Hidden Weights:
	-0.8337670587766758	1.0163000270422693
	0.3338993047995915	-0.5989681937959318
		>50K		<=50K

Error sum for iteration 32500 = 56.50984475740529

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7029293569528743	-0.6649709065047918	age
Hidden Weights:
	-0.833764544330579	1.0162975123824634
	0.3338940037879753	-0.5989628927686778
		>50K		<=50K

Error sum for iteration 32600 = 56.50984471279043

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7030965315061659	-0.6650603990372641	age
Hidden Weights:
	-0.8337620374940639	1.0162950053332789
	0.33388871140217274	-0.5989576003672599
		>50K		<=50K

Error sum for iteration 32700 = 56.509844668429366

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7032631981608813	-0.6651497441741153	age
Hidden Weights:
	-0.8337595382209205	1.0162925058484733
	0.33388342761385076	-0.5989523165634036
		>50K		<=50K

Error sum for iteration 32800 = 56.50984462431999

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7034293600045574	-0.6652389424019262	age
Hidden Weights:
	-0.8337570464653381	1.016290013882256
	0.33387815239483365	-0.5989470413289166
		>50K		<=50K

Error sum for iteration 32900 = 56.50984458046011

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7035950200965881	-0.665327994204788	age
Hidden Weights:
	-0.833754562181931	1.0162875293892173
	0.33387288571711105	-0.5989417746358144
		>50K		<=50K

Error sum for iteration 33000 = 56.50984453684767

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7037601814685536	-0.6654169000644462	age
Hidden Weights:
	-0.8337520853257223	1.0162850523243832
	0.3338676275527526	-0.5989365164561447
		>50K		<=50K

Error sum for iteration 33100 = 56.50984449348025

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7039248471246766	-0.6655056604602204	age
Hidden Weights:
	-0.8337496158521523	1.0162825826431654
	0.3338623778740139	-0.5989312667621067
		>50K		<=50K

Error sum for iteration 33200 = 56.509844450355985

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7040890200420159	-0.6655942758691468	age
Hidden Weights:
	-0.8337471537170352	1.0162801203014014
	0.3338571366532651	-0.5989260255261774
		>50K		<=50K

Error sum for iteration 33300 = 56.50984440747273

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7042527031708739	-0.6656827467658569	age
Hidden Weights:
	-0.833744698876608	1.0162776652552772
	0.33385190386304936	-0.5989207927207717
		>50K		<=50K

Error sum for iteration 33400 = 56.50984436482836

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7044158994351295	-0.665771073622715	age
Hidden Weights:
	-0.8337422512874787	1.016275217461445
	0.3338466794759622	-0.5989155683185382
		>50K		<=50K

Error sum for iteration 33500 = 56.509844322420754

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7045786117325497	-0.6658592569097033	age
Hidden Weights:
	-0.8337398109066655	1.0162727768768767
	0.3338414634647802	-0.5989103522922342
		>50K		<=50K

Error sum for iteration 33600 = 56.50984428024795

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7047408429350099	-0.6659472970944986	age
Hidden Weights:
	-0.8337373776915377	1.0162703434589502
	0.3338362558024084	-0.5989051446148685
		>50K		<=50K

Error sum for iteration 33700 = 56.509844238308006

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7049025958889017	-0.6660351946425686	age
Hidden Weights:
	-0.8337349515998651	1.016267917165425
	0.33383105646191946	-0.5988999452594638
		>50K		<=50K

Error sum for iteration 33800 = 56.509844196598905

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7050638734153538	-0.6661229500170475	age
Hidden Weights:
	-0.8337325325897915	1.016265497954439
	0.3338258654164569	-0.5988947541991392
		>50K		<=50K

Error sum for iteration 33900 = 56.50984415511877

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7052246783106452	-0.6662105636788026	age
Hidden Weights:
	-0.8337301206198137	1.0162630857844803
	0.333820682639331	-0.5988895714072346
		>50K		<=50K

Error sum for iteration 34000 = 56.50984411386544

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7053850133463327	-0.6662980360864982	age
Hidden Weights:
	-0.8337277156488115	1.0162606806144228
	0.33381550810397204	-0.5988843968570956
		>50K		<=50K

Error sum for iteration 34100 = 56.50984407283711

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7055448812697196	-0.6663853676965842	age
Hidden Weights:
	-0.83372531763602	1.0162582824034787
	0.33381034178395474	-0.5988792305224226
		>50K		<=50K

Error sum for iteration 34200 = 56.509844032031936

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7057042848040177	-0.6664725589632399	age
Hidden Weights:
	-0.8337229265410143	1.0162558911112556
	0.33380518365295747	-0.5988740723768027
		>50K		<=50K

Error sum for iteration 34300 = 56.50984399144807

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.705863226648695	-0.666559610338534	age
Hidden Weights:
	-0.8337205423237389	1.0162535066976504
	0.3338000336848009	-0.598868922394093
		>50K		<=50K

Error sum for iteration 34400 = 56.50984395108364

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7060217094796399	-0.6666465222722553	age
Hidden Weights:
	-0.833718164944474	1.0162511291229779
	0.33379489185341615	-0.5988637805481302
		>50K		<=50K

Error sum for iteration 34500 = 56.50984391093668

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7061797359495964	-0.6667332952120497	age
Hidden Weights:
	-0.8337157943638613	1.0162487583478303
	0.3337897581328517	-0.5988586468130631
		>50K		<=50K

Error sum for iteration 34600 = 56.50984387100568

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7063373086882944	-0.6668199296034761	age
Hidden Weights:
	-0.8337134305428705	1.0162463943331956
	0.33378463249732954	-0.5988535211631031
		>50K		<=50K

Error sum for iteration 34700 = 56.50984383128868

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7064944303027839	-0.6669064258898968	age
Hidden Weights:
	-0.8337110734428068	1.0162440370403543
	0.333779514921128	-0.5988484035725206
		>50K		<=50K

Error sum for iteration 34800 = 56.509843791783624

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7066511033777626	-0.6669927845125708	age
Hidden Weights:
	-0.8337087230253031	1.016241686430958
	0.33377440537867953	-0.5988432940157903
		>50K		<=50K

Error sum for iteration 34900 = 56.509843752489374

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7068073304756419	-0.6670790059105801	age
Hidden Weights:
	-0.8337063792523265	1.0162393424669487
	0.3337693038445744	-0.5988381924674144
		>50K		<=50K

Error sum for iteration 35000 = 56.50984371340368

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7069631141368999	-0.667165090520979	age
Hidden Weights:
	-0.8337040420861753	1.0162370051106377
	0.33376421029348213	-0.5988330989020523
		>50K		<=50K

Error sum for iteration 35100 = 56.50984367452514

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7071184568804032	-0.6672510387786568	age
Hidden Weights:
	-0.8337017114894589	1.0162346743246027
	0.33375912470016716	-0.598828013294514
		>50K		<=50K

Error sum for iteration 35200 = 56.50984363585201

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7072733612035981	-0.6673368511165646	age
Hidden Weights:
	-0.833699387425114	1.016232350071772
	0.33375404703956874	-0.5988229356197419
		>50K		<=50K

Error sum for iteration 35300 = 56.50984359738254

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7074278295827198	-0.6674225279654474	age
Hidden Weights:
	-0.8336970698563679	1.0162300323154019
	0.333748977286731	-0.5988178658528064
		>50K		<=50K

Error sum for iteration 35400 = 56.509843559115026

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7075818644729921	-0.6675080697540652	age
Hidden Weights:
	-0.8336947587467898	1.0162277210190174
	0.33374391541680176	-0.598812803968811
		>50K		<=50K

Error sum for iteration 35500 = 56.5098435210479

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7077354683090465	-0.667593476909155	age
Hidden Weights:
	-0.8336924540602302	1.016225416146498
	0.33373886140505044	-0.5988077499430674
		>50K		<=50K

Error sum for iteration 35600 = 56.50984348317961

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7078886435049276	-0.6676787498554091	age
Hidden Weights:
	-0.833690155760862	1.0162231176619785
	0.3337338152268869	-0.5988027037509374
		>50K		<=50K

Error sum for iteration 35700 = 56.50984344550862

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7080413924545129	-0.6677638890155447	age
Hidden Weights:
	-0.8336878638131278	1.0162208255299179
	0.3337287768577901	-0.5987976653679009
		>50K		<=50K

Error sum for iteration 35800 = 56.50984340803305

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7081937175316708	-0.6678488948102259	age
Hidden Weights:
	-0.8336855781818111	1.0162185397150791
	0.33372374627338164	-0.5987926347695629
		>50K		<=50K

Error sum for iteration 35900 = 56.50984337075171

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7083456210903635	-0.6679337676581744	age
Hidden Weights:
	-0.8336832988319467	1.0162162601825109
	0.33371872344939996	-0.5987876119316912
		>50K		<=50K

Error sum for iteration 36000 = 56.509843333662744

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7084971054650748	-0.6680185079761677	age
Hidden Weights:
	-0.8336810257288877	1.016213986897547
	0.33371370836168784	-0.5987825968301634
		>50K		<=50K

Error sum for iteration 36100 = 56.509843296764835

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7086481729708795	-0.6681031161789542	age
Hidden Weights:
	-0.8336787588382671	1.016211719825798
	0.3337087009861962	-0.5987775894409271
		>50K		<=50K

Error sum for iteration 36200 = 56.509843260056265

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7087988259036812	-0.6681875926793294	age
Hidden Weights:
	-0.833676498125982	1.0162094589331905
	0.3337037012990104	-0.5987725897400188
		>50K		<=50K

Error sum for iteration 36300 = 56.50984322353571

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7089490665404501	-0.6682719378882304	age
Hidden Weights:
	-0.833674243558232	1.0162072041858863
	0.33369870927631307	-0.598767597703687
		>50K		<=50K

Error sum for iteration 36400 = 56.509843187201554

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7090988971394844	-0.66835615221457	age
Hidden Weights:
	-0.8336719951014957	1.0162049555503792
	0.3336937248943954	-0.5987626133082078
		>50K		<=50K

Error sum for iteration 36500 = 56.50984315105266

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7092483199405304	-0.6684402360654544	age
Hidden Weights:
	-0.8336697527225211	1.0162027129933895
	0.3336887481296704	-0.5987576365299709
		>50K		<=50K

Error sum for iteration 36600 = 56.509843115087065

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7093973371649479	-0.6685241898460178	age
Hidden Weights:
	-0.8336675163883074	1.016200476481948
	0.3336837789586668	-0.5987526673455256
		>50K		<=50K

Error sum for iteration 36700 = 56.509843079303785

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7095459510159967	-0.6686080139595635	age
Hidden Weights:
	-0.8336652860661494	1.0161982459833236
	0.3336788173579962	-0.598747705731424
		>50K		<=50K

Error sum for iteration 36800 = 56.5098430437012

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7096941636790431	-0.6686917088075073	age
Hidden Weights:
	-0.8336630617235959	1.0161960214650525
	0.33367386330438914	-0.5987427516644422
		>50K		<=50K

Error sum for iteration 36900 = 56.50984300827774

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7098419773217456	-0.6687752747893972	age
Hidden Weights:
	-0.8336608433284698	1.0161938028949473
	0.33366891677465815	-0.5987378051214053
		>50K		<=50K

Error sum for iteration 37000 = 56.509842973032235

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7099893940941219	-0.6688587123028928	age
Hidden Weights:
	-0.8336586308488286	1.0161915902410934
	0.33366397774579115	-0.5987328660791801
		>50K		<=50K

Error sum for iteration 37100 = 56.50984293796331

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7101364161289329	-0.6689420217438555	age
Hidden Weights:
	-0.8336564242530055	1.0161893834718025
	0.3336590461948068	-0.598727934514904
		>50K		<=50K

Error sum for iteration 37200 = 56.509842903069654

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7102830455417408	-0.6690252035063236	age
Hidden Weights:
	-0.8336542235095972	1.016187182555648
	0.3336541220988953	-0.5987230104057621
		>50K		<=50K

Error sum for iteration 37300 = 56.50984286834974

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.71042928443108	-0.6691082579824655	age
Hidden Weights:
	-0.8336520285874266	1.0161849874614604
	0.333649205435312	-0.5987180937289466
		>50K		<=50K

Error sum for iteration 37400 = 56.50984283380237

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7105751348787563	-0.669191185562699	age
Hidden Weights:
	-0.8336498394555941	1.0161827981583225
	0.3336442961813916	-0.5987131844619509
		>50K		<=50K

Error sum for iteration 37500 = 56.50984279942612

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7107205989498507	-0.6692739866355755	age
Hidden Weights:
	-0.8336476560834084	1.016180614615568
	0.33363939431463296	-0.5987082825821749
		>50K		<=50K

Error sum for iteration 37600 = 56.5098427652198

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7108656786931212	-0.6693566615878822	age
Hidden Weights:
	-0.8336454784404568	1.0161784368027544
	0.33363449981262777	-0.5987033880671369
		>50K		<=50K

Error sum for iteration 37700 = 56.509842731181934

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7110103761410171	-0.6694392108046839	age
Hidden Weights:
	-0.8336433064965535	1.0161762646897043
	0.33362961265301877	-0.5986985008945294
		>50K		<=50K

Error sum for iteration 37800 = 56.509842697311505

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7111546933098367	-0.6695216346693305	age
Hidden Weights:
	-0.8336411402217468	1.0161740982464587
	0.333624732813597	-0.598693621042191
		>50K		<=50K

Error sum for iteration 37900 = 56.50984266360709

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7112986321999721	-0.669603933563274	age
Hidden Weights:
	-0.8336389795863365	1.0161719374433082
	0.3336198602722621	-0.598688748487899
		>50K		<=50K

Error sum for iteration 38000 = 56.509842630067425

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7114421947960434	-0.6696861078662739	age
Hidden Weights:
	-0.8336368245608432	1.0161697822507794
	0.33361499500694525	-0.5986838832097544
		>50K		<=50K

Error sum for iteration 38100 = 56.50984259669134

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7115853830670897	-0.6697681579565041	age
Hidden Weights:
	-0.8336346751160153	1.0161676326396094
	0.3336101369957501	-0.5986790251857561
		>50K		<=50K

Error sum for iteration 38200 = 56.50984256347764

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7117281989667087	-0.6698500842101968	age
Hidden Weights:
	-0.8336325312228361	1.0161654885807672
	0.3336052862168792	-0.5986741743940946
		>50K		<=50K

Error sum for iteration 38300 = 56.509842530424834

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7118706444332334	-0.6699318870019436	age
Hidden Weights:
	-0.8336303928525285	1.0161633500454803
	0.3336004426485738	-0.5986693308130618
		>50K		<=50K

Error sum for iteration 38400 = 56.50984249753213

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7120127213899033	-0.6700135667047088	age
Hidden Weights:
	-0.8336282599765128	1.0161612170051695
	0.3335956062692189	-0.5986644944210398
		>50K		<=50K

Error sum for iteration 38500 = 56.50984246479812

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7121544317449537	-0.6700951236897212	age
Hidden Weights:
	-0.833626132566447	1.0161590894314745
	0.3335907770572954	-0.5986596651964858
		>50K		<=50K

Error sum for iteration 38600 = 56.50984243222157

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7122957773918346	-0.6701765583265273	age
Hidden Weights:
	-0.8336240105941997	1.0161569672962738
	0.3335859549913715	-0.5986548431180029
		>50K		<=50K

Error sum for iteration 38700 = 56.50984239980142

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7124367602093684	-0.670257870983024	age
Hidden Weights:
	-0.8336218940318735	1.0161548505716413
	0.33358114005011785	-0.5986500281641985
		>50K		<=50K

Error sum for iteration 38800 = 56.50984236753647

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7125773820618081	-0.6703390620254185	age
Hidden Weights:
	-0.8336197828517691	1.0161527392299055
	0.333576332212294	-0.5986452203138931
		>50K		<=50K

Error sum for iteration 38900 = 56.50984233542561

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7127176447991509	-0.6704201318182984	age
Hidden Weights:
	-0.8336176770264008	1.0161506332435566
	0.33357153145674506	-0.5986404195458823
		>50K		<=50K

Error sum for iteration 39000 = 56.50984230346766

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7128575502571479	-0.6705010807245745	age
Hidden Weights:
	-0.8336155765285058	1.0161485325853477
	0.3335667377624356	-0.5986356258391309
		>50K		<=50K

Error sum for iteration 39100 = 56.50984227166158

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7129971002574562	-0.6705819091055674	age
Hidden Weights:
	-0.833613481331018	1.0161464372281714
	0.33356195110840486	-0.5986308391727002
		>50K		<=50K

Error sum for iteration 39200 = 56.50984224000614

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7131362966078473	-0.670662617320961	age
Hidden Weights:
	-0.8336113914070794	1.0161443471452127
	0.33355717147380887	-0.5986260595257344
		>50K		<=50K

Error sum for iteration 39300 = 56.50984220850029

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7132751411023519	-0.6707432057288193	age
Hidden Weights:
	-0.8336093067300497	1.0161422623097922
	0.3335523988378632	-0.5986212868774491
		>50K		<=50K

Error sum for iteration 39400 = 56.50984217714307

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7134136355213664	-0.6708236746856308	age
Hidden Weights:
	-0.8336072272734587	1.016140182695444
	0.33354763317987446	-0.598616521207153
		>50K		<=50K

Error sum for iteration 39500 = 56.50984214593322

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7135517816317362	-0.6709040245462887	age
Hidden Weights:
	-0.8336051530110704	1.016138108275932
	0.33354287447926473	-0.5986117624942936
		>50K		<=50K

Error sum for iteration 39600 = 56.509842114869805

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7136895811869521	-0.6709842556641031	age
Hidden Weights:
	-0.8336030839168179	1.0161360390251877
	0.333538122715558	-0.5986070107183429
		>50K		<=50K

Error sum for iteration 39700 = 56.50984208395163

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7138270359273444	-0.6710643683907859	age
Hidden Weights:
	-0.8336010199648709	1.0161339749173557
	0.3335333778683685	-0.5986022658588926
		>50K		<=50K

Error sum for iteration 39800 = 56.509842053177834

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7139641475801043	-0.671144363076492	age
Hidden Weights:
	-0.8335989611295498	1.0161319159267654
	0.33352863991734766	-0.5985975278957031
		>50K		<=50K

Error sum for iteration 39900 = 56.5098420225473

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7141009178594829	-0.671224240069837	age
Hidden Weights:
	-0.8335969073853748	1.0161298620279526
	0.33352390884227606	-0.5985927968084912
		>50K		<=50K

Error sum for iteration 40000 = 56.50984199205887

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7142373484668267	-0.6713039997179037	age
Hidden Weights:
	-0.8335948587070807	1.0161278131956326
	0.3335191846230208	-0.5985880725771621
		>50K		<=50K

Error sum for iteration 40100 = 56.5098419617118

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7143734410908077	-0.6713836423662127	age
Hidden Weights:
	-0.8335928150695696	1.0161257694046928
	0.3335144672395351	-0.5985833551816491
		>50K		<=50K

Error sum for iteration 40200 = 56.509841931504795

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7145091974075812	-0.6714631683587672	age
Hidden Weights:
	-0.8335907764479451	1.0161237306302497
	0.3335097566718807	-0.5985786446019885
		>50K		<=50K

Error sum for iteration 40300 = 56.509841901437014

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7146446190808217	-0.6715425780380913	age
Hidden Weights:
	-0.8335887428174757	1.016121696847568
	0.33350505290017907	-0.5985739408183082
		>50K		<=50K

Error sum for iteration 40400 = 56.509841871507405

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7147797077619021	-0.6716218717451679	age
Hidden Weights:
	-0.8335867141536255	1.0161196680320908
	0.33350035590466187	-0.598569243810862
		>50K		<=50K

Error sum for iteration 40500 = 56.50984184171512

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7149144650899355	-0.671701049819488	age
Hidden Weights:
	-0.833584690432044	1.0161176441594666
	0.3334956656656158	-0.5985645535599478
		>50K		<=50K

Error sum for iteration 40600 = 56.509841812059044

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7150488926919476	-0.6717801125989991	age
Hidden Weights:
	-0.8335826716285438	1.0161156252055183
	0.3334909821634671	-0.5985598700459341
		>50K		<=50K

Error sum for iteration 40700 = 56.5098417825383

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7151829921830261	-0.6718590604202657	age
Hidden Weights:
	-0.8335806577191304	1.016113611146258
	0.33348630537866963	-0.5985551932493437
		>50K		<=50K

Error sum for iteration 40800 = 56.509841753151996

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7153167651663592	-0.671937893618319	age
Hidden Weights:
	-0.8335786486799851	1.0161116019578227
	0.3334816352917911	-0.5985505231506445
		>50K		<=50K

Error sum for iteration 40900 = 56.50984172389901

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7154502132334617	-0.67201661252673	age
Hidden Weights:
	-0.8335766444874471	1.0161095976165841
	0.33347697188349185	-0.5985458597305656
		>50K		<=50K

Error sum for iteration 41000 = 56.50984169477846

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7155833379641383	-0.6720952174775959	age
Hidden Weights:
	-0.8335746451180361	1.016107598099054
	0.33347231513447034	-0.5985412029698073
		>50K		<=50K

Error sum for iteration 41100 = 56.509841665789665

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.715716140926775	-0.6721737088016043	age
Hidden Weights:
	-0.8335726505484495	1.0161056033819311
	0.33346766502556585	-0.5985365528492278
		>50K		<=50K

Error sum for iteration 41200 = 56.50984163693152

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7158486236783376	-0.6722520868279933	age
Hidden Weights:
	-0.8335706607555509	1.0161036134420534
	0.33346302153764656	-0.5985319093496679
		>50K		<=50K

Error sum for iteration 41300 = 56.50984160820295

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7159807877644881	-0.672330351884586	age
Hidden Weights:
	-0.8335686757163693	1.0161016282564606
	0.3334583846517103	-0.5985272724521182
		>50K		<=50K

Error sum for iteration 41400 = 56.509841579603375

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7161126347197169	-0.6724085042976888	age
Hidden Weights:
	-0.8335666954080866	1.016099647802312
	0.333453754348811	-0.5985226421376392
		>50K		<=50K

Error sum for iteration 41500 = 56.50984155113171

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7162441660674165	-0.6724865443923419	age
Hidden Weights:
	-0.8335647198080738	1.0160976720570014
	0.333449130610106	-0.5985180183873787
		>50K		<=50K

Error sum for iteration 41600 = 56.50984152278713

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7163753833200147	-0.6725644724920953	age
Hidden Weights:
	-0.833562748893839	1.016095700998016
	0.3334445134167911	-0.5985134011825832
		>50K		<=50K

Error sum for iteration 41700 = 56.50984149456886

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7165062879791352	-0.6726422889190243	age
Hidden Weights:
	-0.833560782643074	1.0160937346030559
	0.3334399027501824	-0.5985087905045419
		>50K		<=50K

Error sum for iteration 41800 = 56.50984146647588

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.716636881535613	-0.6727199939939654	age
Hidden Weights:
	-0.8335588210336191	1.0160917728499466
	0.33343529859168686	-0.5985041863346517
		>50K		<=50K

Error sum for iteration 41900 = 56.5098414385074

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7167671654696038	-0.672797588036311	age
Hidden Weights:
	-0.8335568640434742	1.0160898157166856
	0.3334307009227423	-0.5984995886543479
		>50K		<=50K

Error sum for iteration 42000 = 56.50984141066253

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7168971412507523	-0.6728750713640655	age
Hidden Weights:
	-0.8335549116507953	1.0160878631814443
	0.33342610972494235	-0.5984949974451298
		>50K		<=50K

Error sum for iteration 42100 = 56.50984138294057

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7170268103382349	-0.6729524442939012	age
Hidden Weights:
	-0.8335529638338861	1.0160859152225163
	0.33342152497987815	-0.598490412688686
		>50K		<=50K

Error sum for iteration 42200 = 56.50984135534045

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7171561741808807	-0.673029707141075	age
Hidden Weights:
	-0.8335510205712122	1.0160839718183428
	0.3334169466692333	-0.5984858343667075
		>50K		<=50K

Error sum for iteration 42300 = 56.50984132786149

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7172852342172408	-0.673106860219508	age
Hidden Weights:
	-0.8335490818413939	1.016082032947559
	0.3334123747748058	-0.5984812624609559
		>50K		<=50K

Error sum for iteration 42400 = 56.50984130050298

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7174139918757484	-0.673183903841845	age
Hidden Weights:
	-0.8335471476231917	1.01608009858891
	0.3334078092784412	-0.5984766969533423
		>50K		<=50K

Error sum for iteration 42500 = 56.50984127326385

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7175424485747618	-0.6732608383193213	age
Hidden Weights:
	-0.8335452178955238	1.0160781687213347
	0.33340325016207567	-0.5984721378257799
		>50K		<=50K

Error sum for iteration 42600 = 56.50984124614356

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7176706057226205	-0.6733376639618492	age
Hidden Weights:
	-0.8335432926374619	1.0160762433238681
	0.3333986974077333	-0.5984675850602978
		>50K		<=50K

Error sum for iteration 42700 = 56.509841219141116

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7177984647178609	-0.6734143810780956	age
Hidden Weights:
	-0.8335413718282053	1.016074322375749
	0.33339415099751313	-0.5984630386389566
		>50K		<=50K

Error sum for iteration 42800 = 56.509841192256

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7179260269492067	-0.6734909899753059	age
Hidden Weights:
	-0.8335394554471172	1.0160724058562964
	0.33338961091354735	-0.5984584985439411
		>50K		<=50K

Error sum for iteration 42900 = 56.50984116548709

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7180532937956916	-0.6735674909595167	age
Hidden Weights:
	-0.8335375434736847	1.016070493745031
	0.3333850771380939	-0.5984539647574613
		>50K		<=50K

Error sum for iteration 43000 = 56.50984113883377

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7181802666267044	-0.6736438843353988	age
Hidden Weights:
	-0.8335356358875636	1.0160685860215684
	0.3333805496534739	-0.5984494372618582
		>50K		<=50K

Error sum for iteration 43100 = 56.509841112295256

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7183069468021621	-0.6737201704063681	age
Hidden Weights:
	-0.8335337326685325	1.0160666826656948
	0.3333760284420671	-0.5984449160395138
		>50K		<=50K

Error sum for iteration 43200 = 56.50984108587074

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7184333356725678	-0.6737963494745627	age
Hidden Weights:
	-0.8335318337965157	1.0160647836573415
	0.33337151348633354	-0.5984404010728887
		>50K		<=50K

Error sum for iteration 43300 = 56.50984105955959

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7185594345791037	-0.6738724218408145	age
Hidden Weights:
	-0.8335299392515516	1.01606288897655
	0.333367004768835	-0.5984358923445133
		>50K		<=50K

Error sum for iteration 43400 = 56.509841033361035

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7186852448536339	-0.6739483878046981	age
Hidden Weights:
	-0.8335280490138649	1.016060998603527
	0.33336250227215386	-0.5984313898369714
		>50K		<=50K

Error sum for iteration 43500 = 56.50984100727442

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7188107678188808	-0.6740242476645288	age
Hidden Weights:
	-0.8335261630637695	1.016059112518608
	0.33335800597900955	-0.5984268935329483
		>50K		<=50K

Error sum for iteration 43600 = 56.50984098129866

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7189360047885045	-0.6741000017174177	age
Hidden Weights:
	-0.8335242813817463	1.0160572307022266
	0.3333535158721163	-0.5984224034151955
		>50K		<=50K

Error sum for iteration 43700 = 56.50984095543338

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7190609570671804	-0.6741756502591242	age
Hidden Weights:
	-0.8335224039483952	1.0160553531349992
	0.3333490319342966	-0.5984179194665608
		>50K		<=50K

Error sum for iteration 43800 = 56.50984092967776

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7191856259505988	-0.6742511935842418	age
Hidden Weights:
	-0.8335205307444472	1.0160534797976797
	0.33334455414844905	-0.5984134416699284
		>50K		<=50K

Error sum for iteration 43900 = 56.509840904031066

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7193100127256468	-0.6743266319861021	age
Hidden Weights:
	-0.8335186617507656	1.0160516106711055
	0.3333400824975571	-0.5984089700082917
		>50K		<=50K

Error sum for iteration 44000 = 56.50984087849243

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7194341186704766	-0.674401965756816	age
Hidden Weights:
	-0.8335167969483483	1.0160497457362747
	0.3333356169646719	-0.5984045044646901
		>50K		<=50K

Error sum for iteration 44100 = 56.5098408530615

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7195579450545416	-0.6744771951873234	age
Hidden Weights:
	-0.8335149363183236	1.01604788497431
	0.3333311575328973	-0.5984000450221506
		>50K		<=50K

Error sum for iteration 44200 = 56.509840827737335

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.719681493138711	-0.6745523205672835	age
Hidden Weights:
	-0.8335130798419422	1.016046028366471
	0.33332670418541105	-0.5983955916639718
		>50K		<=50K

Error sum for iteration 44300 = 56.50984080251941

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7198047641752602	-0.6746273421851389	age
Hidden Weights:
	-0.8335112275005705	1.016044175894109
	0.3333222569054635	-0.5983911443733403
		>50K		<=50K

Error sum for iteration 44400 = 56.509840777406744

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7199277594081547	-0.6747022603281457	age
Hidden Weights:
	-0.8335093792757226	1.0160423275387405
	0.33331781567638336	-0.5983867031336301
		>50K		<=50K

Error sum for iteration 44500 = 56.509840752398965

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7200504800728691	-0.6747770752824708	age
Hidden Weights:
	-0.8335075351490187	1.0160404832819914
	0.33331338048154097	-0.598382267928162
		>50K		<=50K

Error sum for iteration 44600 = 56.509840727495195

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7201729273966593	-0.6748517873329943	age
Hidden Weights:
	-0.8335056951022152	1.0160386431056023
	0.3333089513044159	-0.5983778387404179
		>50K		<=50K

Error sum for iteration 44700 = 56.50984070269496

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7202951025985757	-0.674926396763398	age
Hidden Weights:
	-0.8335038591171744	1.016036806991434
	0.3333045281285216	-0.5983734155539715
		>50K		<=50K

Error sum for iteration 44800 = 56.50984067799753

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7204170068894152	-0.6750009038562528	age
Hidden Weights:
	-0.8335020271759003	1.01603497492149
	0.33330011093744855	-0.5983689983524141
		>50K		<=50K

Error sum for iteration 44900 = 56.509840653402215

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7205386414719719	-0.6750753088929138	age
Hidden Weights:
	-0.8335001992605032	1.0160331468778752
	0.3332956997148497	-0.5983645871193414
		>50K		<=50K

Error sum for iteration 45000 = 56.50984062890829

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7206600075410439	-0.6751496121535673	age
Hidden Weights:
	-0.8334983753532057	1.0160313228428126
	0.33329129444446043	-0.5983601818385135
		>50K		<=50K

Error sum for iteration 45100 = 56.50984060451525

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7207811062835313	-0.6752238139173239	age
Hidden Weights:
	-0.8334965554363586	1.0160295027986592
	0.33328689511006787	-0.5983557824937047
		>50K		<=50K

Error sum for iteration 45200 = 56.5098405802224

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7209019388783681	-0.6752979144620894	age
Hidden Weights:
	-0.8334947394924334	1.016027686727867
	0.3332825016955502	-0.598351389068833
		>50K		<=50K

Error sum for iteration 45300 = 56.50984055602908

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7210225064967648	-0.6753719140646334	age
Hidden Weights:
	-0.8334929275040125	1.0160258746130377
	0.3332781141848258	-0.5983470015477976
		>50K		<=50K

Error sum for iteration 45400 = 56.509840531934685

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7211428103022016	-0.675445813000568	age
Hidden Weights:
	-0.8334911194537803	1.0160240664368472
	0.33327373256192955	-0.5983426199145594
		>50K		<=50K

Error sum for iteration 45500 = 56.50984050793867

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7212628514505086	-0.6755196115444158	age
Hidden Weights:
	-0.8334893153245623	1.0160222621821038
	0.3332693568108725	-0.5983382441532578
		>50K		<=50K

Error sum for iteration 45600 = 56.509840484040396

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7213826310899487	-0.6755933099695691	age
Hidden Weights:
	-0.8334875150992699	1.016020461831722
	0.3332649869157948	-0.5983338742479609
		>50K		<=50K

Error sum for iteration 45700 = 56.50984046023916

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7215021503612032	-0.6756669085482876	age
Hidden Weights:
	-0.8334857187609492	1.0160186653687453
	0.33326062286087743	-0.5983295101828257
		>50K		<=50K

Error sum for iteration 45800 = 56.50984043653437

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7216214103974873	-0.6757404075517078	age
Hidden Weights:
	-0.8334839262927296	1.0160168727762948
	0.3332562646303744	-0.5983251519421453
		>50K		<=50K

Error sum for iteration 45900 = 56.50984041292551

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7217404123246941	-0.6758138072499698	age
Hidden Weights:
	-0.8334821376778603	1.016015084037638
	0.33325191220858474	-0.5983207995102293
		>50K		<=50K

Error sum for iteration 46000 = 56.50984038941195

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7218591572613476	-0.6758871079119463	age
Hidden Weights:
	-0.833480352899723	1.0160132991361364
	0.33324756557991364	-0.5983164528714503
		>50K		<=50K

Error sum for iteration 46100 = 56.50984036599317

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7219776463187414	-0.6759603098055221	age
Hidden Weights:
	-0.8334785719417722	1.0160115180552516
	0.3332432247287994	-0.5983121120102058
		>50K		<=50K

Error sum for iteration 46200 = 56.5098403426684

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7220958806009538	-0.6760334131974827	age
Hidden Weights:
	-0.8334767947875875	1.016009740778564
	0.3332388896397492	-0.5983077769110501
		>50K		<=50K

Error sum for iteration 46300 = 56.509840319437174

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7222138612048801	-0.6761064183535109	age
Hidden Weights:
	-0.8334750214208602	1.016007967289745
	0.33323456029732373	-0.5983034475585548
		>50K		<=50K

Error sum for iteration 46400 = 56.50984029629896

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7223315892203769	-0.6761793255382241	age
Hidden Weights:
	-0.8334732518253749	1.0160061975725871
	0.33323023668613366	-0.59829912393729
		>50K		<=50K

Error sum for iteration 46500 = 56.50984027325297

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7224490657302733	-0.6762521350151777	age
Hidden Weights:
	-0.8334714859850196	1.0160044316109949
	0.3332259187909037	-0.5982948060320077
		>50K		<=50K

Error sum for iteration 46600 = 56.509840250298964

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7225662918104895	-0.6763248470468809	age
Hidden Weights:
	-0.8334697238837844	1.016002669388924
	0.3332216065963573	-0.5982904938274822
		>50K		<=50K

Error sum for iteration 46700 = 56.50984022743609

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7226832685299603	-0.6763974618947003	age
Hidden Weights:
	-0.833467965505774	1.0160009108904984
	0.3332173000873169	-0.5982861873085362
		>50K		<=50K

Error sum for iteration 46800 = 56.509840204664044

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7227999969508793	-0.6764699798190226	age
Hidden Weights:
	-0.8334662108352003	1.0159991560999044
	0.33321299924868264	-0.5982818864600072
		>50K		<=50K

Error sum for iteration 46900 = 56.50984018198215

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7229164781285775	-0.6765424010792213	age
Hidden Weights:
	-0.833464459856341	1.0159974050014473
	0.3332087040653902	-0.598277591266798
		>50K		<=50K

Error sum for iteration 47000 = 56.509840159389924

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7230327131116993	-0.6766147259335743	age
Hidden Weights:
	-0.8334627125536066	1.015995657579516
	0.33320441452239014	-0.5982733017139329
		>50K		<=50K

Error sum for iteration 47100 = 56.509840136886574

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7231487029421967	-0.6766869546393042	age
Hidden Weights:
	-0.8334609689114909	1.0159939138186085
	0.33320013060474896	-0.5982690177865245
		>50K		<=50K

Error sum for iteration 47200 = 56.50984011447177

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7232644486554202	-0.6767590874526781	age
Hidden Weights:
	-0.8334592289145941	1.0159921737033244
	0.33319585229760873	-0.598264739469601
		>50K		<=50K

Error sum for iteration 47300 = 56.50984009214504

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.723379951280222	-0.6768311246288622	age
Hidden Weights:
	-0.833457492547613	1.0159904372183512
	0.3331915795861349	-0.5982604667483231
		>50K		<=50K

Error sum for iteration 47400 = 56.50984006990578

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7234952118388743	-0.6769030664220335	age
Hidden Weights:
	-0.8334557597953322	1.0159887043484952
	0.33318731245554273	-0.5982561996079775
		>50K		<=50K

Error sum for iteration 47500 = 56.50984004775335

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7236102313472788	-0.6769749130853819	age
Hidden Weights:
	-0.8334540306426428	1.0159869750786046
	0.33318305089113476	-0.5982519380338172
		>50K		<=50K

Error sum for iteration 47600 = 56.509840025687495

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7237250108149071	-0.6770466648710912	age
Hidden Weights:
	-0.83345230507452	1.0159852493936785
	0.33317879487826446	-0.598247682011227
		>50K		<=50K

Error sum for iteration 47700 = 56.509840003707325

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7238395512448984	-0.6771183220302985	age
Hidden Weights:
	-0.8334505830760444	1.0159835272787918
	0.33317454440235567	-0.5982434315255997
		>50K		<=50K

Error sum for iteration 47800 = 56.50983998181279

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.723953853634102	-0.6771898848131629	age
Hidden Weights:
	-0.8334488646323744	1.015981808719095
	0.3331702994488404	-0.5982391865624083
		>50K		<=50K

Error sum for iteration 47900 = 56.50983996000303

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7240679189731412	-0.6772613534688617	age
Hidden Weights:
	-0.8334471497287791	1.0159800936998666
	0.3331660600032493	-0.5982349471071677
		>50K		<=50K

Error sum for iteration 48000 = 56.509839938277636

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7241817482465092	-0.6773327282455819	age
Hidden Weights:
	-0.8334454383506087	1.0159783822064312
	0.33316182605117917	-0.598230713145479
		>50K		<=50K

Error sum for iteration 48100 = 56.50983991663604

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7242953424324933	-0.6774040093905326	age
Hidden Weights:
	-0.8334437304833108	1.0159766742242573
	0.3331575975782506	-0.5982264846630052
		>50K		<=50K

Error sum for iteration 48200 = 56.50983989507782

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7244087025033626	-0.6774751971498593	age
Hidden Weights:
	-0.8334420261124035	1.0159749697388583
	0.33315337457014754	-0.598222261645425
		>50K		<=50K

Error sum for iteration 48300 = 56.50983987360244

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7245218294253266	-0.6775462917688392	age
Hidden Weights:
	-0.8334403252235197	1.0159732687358707
	0.33314915701264225	-0.5982180440784812
		>50K		<=50K

Error sum for iteration 48400 = 56.50983985220965

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7246347241586443	-0.677617293491778	age
Hidden Weights:
	-0.8334386278023648	1.015971571200983
	0.333144944891546	-0.5982138319479873
		>50K		<=50K

Error sum for iteration 48500 = 56.509839830898706

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7247473876576088	-0.6776882025620522	age
Hidden Weights:
	-0.8334369338347524	1.0159698771199945
	0.3331407381927088	-0.5982096252397671
		>50K		<=50K

Error sum for iteration 48600 = 56.509839809669025

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7248598208706544	-0.677759019222016	age
Hidden Weights:
	-0.8334352433065586	1.0159681864788177
	0.3331365369020586	-0.5982054239397108
		>50K		<=50K

Error sum for iteration 48700 = 56.50983978852047

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7249720247404413	-0.677829743713033	age
Hidden Weights:
	-0.8334335562037529	1.0159664992634072
	0.3331323410055523	-0.5982012280338356
		>50K		<=50K

Error sum for iteration 48800 = 56.50983976745239

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7250840002037473	-0.6779003762755723	age
Hidden Weights:
	-0.8334318725124005	1.0159648154598104
	0.33312815048922595	-0.598197037508176
		>50K		<=50K

Error sum for iteration 48900 = 56.50983974646413

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7251957481916481	-0.6779709171491856	age
Hidden Weights:
	-0.8334301922186456	1.0159631350541936
	0.3331239653391551	-0.5981928523487784
		>50K		<=50K

Error sum for iteration 49000 = 56.50983972555553

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7253072696295852	-0.6780413665724839	age
Hidden Weights:
	-0.8334285153087131	1.01596145803275
	0.333119785541463	-0.5981886725417865
		>50K		<=50K

Error sum for iteration 49100 = 56.50983970472608

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7254185654372438	-0.6781117247831078	age
Hidden Weights:
	-0.8334268417689232	1.0159597843818153
	0.3331156110823602	-0.5981844980734274
		>50K		<=50K

Error sum for iteration 49200 = 56.509839683975166

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7255296365288536	-0.6781819920177896	age
Hidden Weights:
	-0.8334251715856591	1.0159581140877654
	0.3331114419480604	-0.5981803289298725
		>50K		<=50K

Error sum for iteration 49300 = 56.5098396633024

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7256404838130714	-0.6782521685123583	age
Hidden Weights:
	-0.8334235047454092	1.0159564471370863
	0.33310727812488405	-0.5981761650974544
		>50K		<=50K

Error sum for iteration 49400 = 56.50983964270743

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7257511081929261	-0.6783222545017166	age
Hidden Weights:
	-0.8334218412347298	1.0159547835163438
	0.33310311959913524	-0.598172006562506
		>50K		<=50K

Error sum for iteration 49500 = 56.50983962218967

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7258615105660715	-0.678392250219804	age
Hidden Weights:
	-0.8334201810402618	1.0159531232121686
	0.33309896635725045	-0.598167853311448
		>50K		<=50K

Error sum for iteration 49600 = 56.509839601748766

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7259716918247318	-0.6784621558997546	age
Hidden Weights:
	-0.8334185241487163	1.0159514662112807
	0.33309481838568233	-0.5981637053307569
		>50K		<=50K

Error sum for iteration 49700 = 56.50983958138418

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7260816528557124	-0.6785319717737116	age
Hidden Weights:
	-0.8334168705469042	1.0159498125004611
	0.3330906756709405	-0.5981595626069177
		>50K		<=50K

Error sum for iteration 49800 = 56.509839561095575

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7261913945405839	-0.6786016980729851	age
Hidden Weights:
	-0.8334152202217108	1.0159481620666029
	0.333086538199575	-0.5981554251264848
		>50K		<=50K

Error sum for iteration 49900 = 56.50983954088248

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7263009177555544	-0.6786713350279792	age
Hidden Weights:
	-0.8334135731600762	1.0159465148966684
	0.3330824059581909	-0.5981512928760552
		>50K		<=50K

Error sum for iteration 50000 = 56.50983952074445

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7264102233716266	-0.67874088286818	age
Hidden Weights:
	-0.8334119293490565	1.0159448709777106
	0.3330782789334607	-0.5981471658423014
		>50K		<=50K

Error sum for iteration 50100 = 56.509839500681124

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.72651931225455	-0.678810341822109	age
Hidden Weights:
	-0.8334102887757551	1.0159432302968003
	0.3330741571120909	-0.5981430440119259
		>50K		<=50K

Error sum for iteration 50200 = 56.50983948069194

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7266281852649701	-0.6788797121175582	age
Hidden Weights:
	-0.8334086514273717	1.0159415928411448
	0.33307004048083577	-0.5981389273717133
		>50K		<=50K

Error sum for iteration 50300 = 56.50983946077664

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7267368432583923	-0.6789489939813802	age
Hidden Weights:
	-0.8334070172911553	1.0159399585979951
	0.3330659290265222	-0.5981348159084505
		>50K		<=50K

Error sum for iteration 50400 = 56.509839440934634

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7268452870851568	-0.6790181876395457	age
Hidden Weights:
	-0.8334053863544656	1.015938327554715
	0.33306182273600604	-0.5981307096090502
		>50K		<=50K

Error sum for iteration 50500 = 56.50983942116569

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7269535175906767	-0.6790872933172516	age
Hidden Weights:
	-0.8334037586047083	1.0159366996987018
	0.3330577215962248	-0.5981266084603314
		>50K		<=50K

Error sum for iteration 50600 = 56.509839401469264

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7270615356153355	-0.6791563112386698	age
Hidden Weights:
	-0.8334021340293762	1.0159350750174667
	0.33305362559410423	-0.5981225124492843
		>50K		<=50K

Error sum for iteration 50700 = 56.50983938184505

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.727169341994521	-0.6792252416272107	age
Hidden Weights:
	-0.8334005126160344	1.0159334534985553
	0.3330495347166926	-0.5981184215629612
		>50K		<=50K

Error sum for iteration 50800 = 56.50983936229262

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7272769375587083	-0.6792940847054236	age
Hidden Weights:
	-0.8333988943523236	1.0159318351295976
	0.33304544895102606	-0.5981143357884176
		>50K		<=50K

Error sum for iteration 50900 = 56.50983934281139

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7273843231335416	-0.6793628406950201	age
Hidden Weights:
	-0.8333972792259539	1.0159302198983216
	0.333041368284225	-0.5981102551127655
		>50K		<=50K

Error sum for iteration 51000 = 56.50983932340119

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7274914995397325	-0.6794315098168432	age
Hidden Weights:
	-0.8333956672246988	1.015928607792501
	0.33303729270343246	-0.5981061795230972
		>50K		<=50K

Error sum for iteration 51100 = 56.509839304061515

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7275984675932076	-0.679500092290877	age
Hidden Weights:
	-0.8333940583364169	1.0159269987999744
	0.33303322219586856	-0.5981021090067217
		>50K		<=50K

Error sum for iteration 51200 = 56.50983928479214

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7277052281051111	-0.6795685883363376	age
Hidden Weights:
	-0.8333924525490385	1.0159253929086625
	0.33302915674880235	-0.5980980435508823
		>50K		<=50K

Error sum for iteration 51300 = 56.50983926559238

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7278117818819586	-0.6796369981715403	age
Hidden Weights:
	-0.8333908498505519	1.0159237901065734
	0.3330250963495232	-0.598093983142886
		>50K		<=50K

Error sum for iteration 51400 = 56.509839246462015

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7279181297254618	-0.6797053220140029	age
Hidden Weights:
	-0.8333892502290188	1.0159221903817692
	0.3330210409853982	-0.5980899277701203
		>50K		<=50K

Error sum for iteration 51500 = 56.509839227400754

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7280242724327323	-0.679773560080478	age
Hidden Weights:
	-0.8333876536725867	1.0159205937223725
	0.3330169906438468	-0.5980858774198745
		>50K		<=50K

Error sum for iteration 51600 = 56.50983920840796

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.728130210796157	-0.6798417125868027	age
Hidden Weights:
	-0.8333860601694428	1.0159190001165965
	0.33301294531228254	-0.5980818320797153
		>50K		<=50K

Error sum for iteration 51700 = 56.509839189483536

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.728235945603635	-0.6799097797480577	age
Hidden Weights:
	-0.8333844697078596	1.0159174095527024
	0.33300890497822727	-0.5980777917370612
		>50K		<=50K

Error sum for iteration 51800 = 56.509839170626876

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7283414776384544	-0.6799777617784787	age
Hidden Weights:
	-0.8333828822761855	1.0159158220190334
	0.3330048696292258	-0.5980737563794537
		>50K		<=50K

Error sum for iteration 51900 = 56.509839151837696

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7284468076794669	-0.6800456588914755	age
Hidden Weights:
	-0.8333812978628095	1.015914237503982
	0.3330008392528348	-0.5980697259945538
		>50K		<=50K

Error sum for iteration 52000 = 56.50983913311576

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7285519365009756	-0.6801134712997206	age
Hidden Weights:
	-0.8333797164562193	1.015912655996027
	0.3329968138367409	-0.5980657005698907
		>50K		<=50K

Error sum for iteration 52100 = 56.50983911446044

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.728656864872796	-0.6801811992150435	age
Hidden Weights:
	-0.833378138044945	1.0159110774836981
	0.3329927933685717	-0.5980616800932066
		>50K		<=50K

Error sum for iteration 52200 = 56.509839095871584

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7287615935604302	-0.6802488428484792	age
Hidden Weights:
	-0.8333765626175921	1.0159095019556115
	0.33298877783608277	-0.5980576645522194
		>50K		<=50K

Error sum for iteration 52300 = 56.50983907734883

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7288661233249001	-0.6803164024103097	age
Hidden Weights:
	-0.8333749901628236	1.0159079294004258
	0.33298476722705217	-0.5980536539346897
		>50K		<=50K

Error sum for iteration 52400 = 56.509839058891735

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7289704549229326	-0.680383878110008	age
Hidden Weights:
	-0.8333734206693812	1.0159063598068463
	0.332980761529296	-0.5980496482285063
		>50K		<=50K

Error sum for iteration 52500 = 56.509839040499834

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7290745891069138	-0.6804512701562213	age
Hidden Weights:
	-0.8333718541260563	1.0159047931637049
	0.3329767607306821	-0.5980456474214505
		>50K		<=50K

Error sum for iteration 52600 = 56.50983902217296

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7291785266249635	-0.6805185787568541	age
Hidden Weights:
	-0.8333702905217105	1.0159032294598616
	0.3329727648191099	-0.5980416515014506
		>50K		<=50K

Error sum for iteration 52700 = 56.5098390039106

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.729282268221024	-0.6805858041190124	age
Hidden Weights:
	-0.8333687298452745	1.0159016686842193
	0.332968773782538	-0.5980376604564851
		>50K		<=50K

Error sum for iteration 52800 = 56.50983898571269

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.729385814634684	-0.6806529464491027	age
Hidden Weights:
	-0.8333671720857289	1.0159001108257695
	0.33296478760897913	-0.5980336742744444
		>50K		<=50K

Error sum for iteration 52900 = 56.50983896757851

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7294891666014358	-0.6807200059527472	age
Hidden Weights:
	-0.8333656172321183	1.0158985558735758
	0.3329608062864306	-0.5980296929435676
		>50K		<=50K

Error sum for iteration 53000 = 56.50983894950809

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7295923248525864	-0.6807869828347777	age
Hidden Weights:
	-0.8333640652735637	1.0158970038167003
	0.3329568298030305	-0.5980257164518064
		>50K		<=50K

Error sum for iteration 53100 = 56.50983893150069

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7296952901153475	-0.6808538772991866	age
Hidden Weights:
	-0.8333625161992207	1.0158954546443577
	0.33295285814686837	-0.5980217447873556
		>50K		<=50K

Error sum for iteration 53200 = 56.50983891355624

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.729798063112774	-0.6809206895492925	age
Hidden Weights:
	-0.8333609699983396	1.0158939083457657
	0.3329488913061577	-0.5980177779383455
		>50K		<=50K

Error sum for iteration 53300 = 56.50983889567447

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7299006445638796	-0.6809874197876926	age
Hidden Weights:
	-0.8333594266601998	1.0158923649102185
	0.332944929269132	-0.5980138158929484
		>50K		<=50K

Error sum for iteration 53400 = 56.50983887785481

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7300030351837254	-0.6810540682161897	age
Hidden Weights:
	-0.8333578861741543	1.0158908243270737
	0.3329409720240171	-0.5980098586395666
		>50K		<=50K

Error sum for iteration 53500 = 56.50983886009705

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7301052356833249	-0.6811206350358513	age
Hidden Weights:
	-0.8333563485296187	1.0158892865857099
	0.332937019559117	-0.5980059061664547
		>50K		<=50K

Error sum for iteration 53600 = 56.50983884240086

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7302072467696807	-0.6811871204469858	age
Hidden Weights:
	-0.8333548137160665	1.0158877516756282
	0.33293307186279814	-0.5980019584618789
		>50K		<=50K

Error sum for iteration 53700 = 56.5098388247659

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7303090691458965	-0.6812535246492375	age
Hidden Weights:
	-0.8333532817230184	1.015886219586337
	0.3329291289234446	-0.5979980155143408
		>50K		<=50K

Error sum for iteration 53800 = 56.509838807191805

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7304107035111308	-0.6813198478414204	age
Hidden Weights:
	-0.8333517525400791	1.0158846903074445
	0.33292519072950083	-0.5979940773121903
		>50K		<=50K

Error sum for iteration 53900 = 56.50983878967841

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7305121505607345	-0.6813860902216682	age
Hidden Weights:
	-0.8333502261568768	1.015883163828574
	0.33292125726941874	-0.5979901438439817
		>50K		<=50K

Error sum for iteration 54000 = 56.50983877222509

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7306134109860672	-0.6814522519873597	age
Hidden Weights:
	-0.8333487025631169	1.0158816401394237
	0.3329173285317205	-0.597986215098189
		>50K		<=50K

Error sum for iteration 54100 = 56.50983875483188

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.730714485474774	-0.6815183333351706	age
Hidden Weights:
	-0.8333471817485661	1.0158801192297817
	0.33291340450499135	-0.5979822910633265
		>50K		<=50K

Error sum for iteration 54200 = 56.50983873749823

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.730815374710685	-0.6815843344610686	age
Hidden Weights:
	-0.8333456637030421	1.01587860108944
	0.3329094851778203	-0.5979783717280228
		>50K		<=50K

Error sum for iteration 54300 = 56.509838720223925

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7309160793739121	-0.6816502555602557	age
Hidden Weights:
	-0.8333441484164135	1.0158770857082775
	0.3329055705388499	-0.5979744570809391
		>50K		<=50K

Error sum for iteration 54400 = 56.509838703008654

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.731016600140691	-0.681716096827258	age
Hidden Weights:
	-0.8333426358786021	1.0158755730762183
	0.3329016605767565	-0.5979705471107253
		>50K		<=50K

Error sum for iteration 54500 = 56.50983868585192

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.73111693768364	-0.681781858455907	age
Hidden Weights:
	-0.8333411260795923	1.0158740631832404
	0.33289775528024235	-0.5979666418061764
		>50K		<=50K

Error sum for iteration 54600 = 56.509838668753886

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7312170926716242	-0.681847540639337	age
Hidden Weights:
	-0.8333396190094241	1.015872556019378
	0.33289385463811527	-0.5979627411560243
		>50K		<=50K

Error sum for iteration 54700 = 56.50983865171379

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7313170657699293	-0.6819131435699817	age
Hidden Weights:
	-0.8333381146581931	1.0158710515747156
	0.3328899586391745	-0.5979588451490557
		>50K		<=50K

Error sum for iteration 54800 = 56.50983863473137

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7314168576400994	-0.681978667439475	age
Hidden Weights:
	-0.8333366130160433	1.0158695498394215
	0.33288606727224485	-0.597954953774162
		>50K		<=50K

Error sum for iteration 54900 = 56.509838617806615

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7315164689401602	-0.6820441124387917	age
Hidden Weights:
	-0.8333351140731696	1.015868050803673
	0.33288218052625357	-0.5979510670202254
		>50K		<=50K

Error sum for iteration 55000 = 56.50983860093891

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7316159003245465	-0.682109478758266	age
Hidden Weights:
	-0.8333336178198282	1.0158665544577468
	0.3328782983900978	-0.5979471848761558
		>50K		<=50K

Error sum for iteration 55100 = 56.50983858412822

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7317151524441348	-0.6821747665876043	age
Hidden Weights:
	-0.8333321242463168	1.0158650607919033
	0.3328744208527403	-0.5979433073309303
		>50K		<=50K

Error sum for iteration 55200 = 56.50983856737399

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7318142259462422	-0.6822399761157399	age
Hidden Weights:
	-0.8333306333430043	1.0158635697965315
	0.3328705479032483	-0.597939434373525
		>50K		<=50K

Error sum for iteration 55300 = 56.50983855067618

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7319131214747093	-0.6823051075309675	age
Hidden Weights:
	-0.8333291451002993	1.0158620814620367
	0.33286667953062393	-0.5979355659929927
		>50K		<=50K

Error sum for iteration 55400 = 56.50983853403435

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7320118396698655	-0.6823701610207805	age
Hidden Weights:
	-0.833327659508662	1.0158605957788678
	0.3328628157239403	-0.5979317021784312
		>50K		<=50K

Error sum for iteration 55500 = 56.50983851744823

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7321103811686139	-0.6824351367721073	age
Hidden Weights:
	-0.8333261765585931	1.01585911273756
	0.3328589564723258	-0.5979278429190026
		>50K		<=50K

Error sum for iteration 55600 = 56.50983850091755

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7322087466044567	-0.6825000349712075	age
Hidden Weights:
	-0.8333246962406728	1.0158576323286572
	0.33285510176495375	-0.5979239882038524
		>50K		<=50K

Error sum for iteration 55700 = 56.5098384844422

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7323069366073914	-0.6825648558036225	age
Hidden Weights:
	-0.8333232185454973	1.0158561545427658
	0.33285125159102463	-0.5979201380222177
		>50K		<=50K

Error sum for iteration 55800 = 56.50983846802161

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7324049518041575	-0.6826295994542421	age
Hidden Weights:
	-0.8333217434637497	1.0158546793705636
	0.33284740593980533	-0.5979162923632668
		>50K		<=50K

Error sum for iteration 55900 = 56.50983845165559

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7325027928180676	-0.6826942661073678	age
Hidden Weights:
	-0.833320270986137	1.0158532068027593
	0.3328435648005516	-0.5979124512163058
		>50K		<=50K

Error sum for iteration 56000 = 56.509838435343895

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.732600460269135	-0.6827588559465045	age
Hidden Weights:
	-0.8333188011034341	1.015851736830113
	0.3328397281625508	-0.5979086145705953
		>50K		<=50K

Error sum for iteration 56100 = 56.509838419086336

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7326979547739993	-0.6828233691546017	age
Hidden Weights:
	-0.8333173338064415	1.0158502694434435
	0.332835896015204	-0.5979047824155626
		>50K		<=50K

Error sum for iteration 56200 = 56.50983840288248

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7327952769460863	-0.6828878059138892	age
Hidden Weights:
	-0.833315869086026	1.0158488046336074
	0.33283206834792556	-0.5979009547406287
		>50K		<=50K

Error sum for iteration 56300 = 56.509838386732085

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7328924273955123	-0.6829521664059829	age
Hidden Weights:
	-0.8333144069330988	1.0158473423915162
	0.33282824515009835	-0.5978971315351789
		>50K		<=50K

Error sum for iteration 56400 = 56.50983837063505

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.73298940672922	-0.6830164508118965	age
Hidden Weights:
	-0.8333129473386071	1.0158458827081134
	0.33282442641119797	-0.5978933127886582
		>50K		<=50K

Error sum for iteration 56500 = 56.50983835459086

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7330862155508796	-0.6830806593119801	age
Hidden Weights:
	-0.8333114902935668	1.015844425574426
	0.33282061212072434	-0.5978894984905675
		>50K		<=50K

Error sum for iteration 56600 = 56.50983833859958

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7331828544609823	-0.6831447920858639	age
Hidden Weights:
	-0.8333100357890285	1.0158429709814942
	0.33281680226825505	-0.5978856886304356
		>50K		<=50K

Error sum for iteration 56700 = 56.50983832266051

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7332793240568461	-0.6832088493126285	age
Hidden Weights:
	-0.8333085838161076	1.0158415189204109
	0.3328129968433548	-0.5978818831979208
		>50K		<=50K

Error sum for iteration 56800 = 56.50983830677355

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7333756249326355	-0.6832728311706432	age
Hidden Weights:
	-0.8333071343659348	1.0158400693823424
	0.3328091958356329	-0.5978780821826138
		>50K		<=50K

Error sum for iteration 56900 = 56.509838290938696

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7334717576794351	-0.683336737837696	age
Hidden Weights:
	-0.8333056874297025	1.0158386223584683
	0.3328053992347404	-0.5978742855741869
		>50K		<=50K

Error sum for iteration 57000 = 56.509838275155346

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7335677228851306	-0.683400569490874	age
Hidden Weights:
	-0.833304242998669	1.0158371778400381
	0.3328016070303674	-0.5978704933623026
		>50K		<=50K

Error sum for iteration 57100 = 56.50983825942345

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7336635211346201	-0.6834643263068538	age
Hidden Weights:
	-0.8333028010641083	1.015835735818334
	0.33279781921226076	-0.5978667055366405
		>50K		<=50K

Error sum for iteration 57200 = 56.509838243742934

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7337591530097048	-0.6835280084614427	age
Hidden Weights:
	-0.8333013616173478	1.0158342962846643
	0.332794035770198	-0.5978629220869933
		>50K		<=50K

Error sum for iteration 57300 = 56.5098382281129

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7338546190891099	-0.6835916161299163	age
Hidden Weights:
	-0.8332999246497789	1.0158328592304353
	0.33279025669394996	-0.5978591430032285
		>50K		<=50K

Error sum for iteration 57400 = 56.50983821253366

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7339499199486179	-0.6836551494869628	age
Hidden Weights:
	-0.8332984901528151	1.0158314246470488
	0.3327864819733668	-0.5978553682751178
		>50K		<=50K

Error sum for iteration 57500 = 56.509838197004775

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7340450561609243	-0.6837186087065792	age
Hidden Weights:
	-0.8332970581179233	1.015829992525988
	0.332782711598273	-0.5978515978925136
		>50K		<=50K

Error sum for iteration 57600 = 56.50983818152606

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.734140028295863	-0.6837819939622418	age
Hidden Weights:
	-0.8332956285366102	1.0158285628587482
	0.332778945558606	-0.5978478318453582
		>50K		<=50K

Error sum for iteration 57700 = 56.50983816609728

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7342348369201993	-0.6838453054267862	age
Hidden Weights:
	-0.8332942014004342	1.0158271356369066
	0.33277518384431537	-0.597844070123606
		>50K		<=50K

Error sum for iteration 57800 = 56.50983815071796

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7343294825978425	-0.6839085432723663	age
Hidden Weights:
	-0.8332927767009995	1.015825710852021
	0.33277142644536034	-0.5978403127172044
		>50K		<=50K

Error sum for iteration 57900 = 56.5098381353882

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7344239658897042	-0.6839717076706457	age
Hidden Weights:
	-0.8332913544299321	1.015824288495768
	0.3327676733517649	-0.5978365596161564
		>50K		<=50K

Error sum for iteration 58000 = 56.509838120107545

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7345182873539189	-0.6840347987926331	age
Hidden Weights:
	-0.833289934578928	1.0158228685597939
	0.33276392455357495	-0.5978328108105417
		>50K		<=50K

Error sum for iteration 58100 = 56.5098381048758

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7346124475456378	-0.6840978168088228	age
Hidden Weights:
	-0.8332885171397174	1.0158214510358368
	0.3327601800408412	-0.597829066290454
		>50K		<=50K

Error sum for iteration 58200 = 56.50983808969264

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7347064470171979	-0.6841607618889584	age
Hidden Weights:
	-0.8332871021040543	1.0158200359156817
	0.3327564398037107	-0.5978253260459913
		>50K		<=50K

Error sum for iteration 58300 = 56.509838074558125

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.734800286318077	-0.6842236342022375	age
Hidden Weights:
	-0.833285689463755	1.0158186231911328
	0.3327527038323664	-0.5978215900672529
		>50K		<=50K

Error sum for iteration 58400 = 56.5098380594715

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.734893965994973	-0.6842864339173974	age
Hidden Weights:
	-0.8332842792106848	1.0158172128540415
	0.33274897211695637	-0.5978178583444215
		>50K		<=50K

Error sum for iteration 58500 = 56.50983804443308

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7349874865917774	-0.684349161202487	age
Hidden Weights:
	-0.8332828713367284	1.015815804896306
	0.3327452446476613	-0.5978141308677724
		>50K		<=50K

Error sum for iteration 58600 = 56.50983802944225

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7350808486496008	-0.6844118162249755	age
Hidden Weights:
	-0.8332814658338299	1.015814399309858
	0.33274152141475893	-0.5978104076275113
		>50K		<=50K

Error sum for iteration 58700 = 56.50983801449903

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7351740527068018	-0.6844743991517621	age
Hidden Weights:
	-0.8332800626939587	1.0158129960866542
	0.33273780240853157	-0.5978066886139435
		>50K		<=50K

Error sum for iteration 58800 = 56.50983799960302

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7352670992990068	-0.6845369101491291	age
Hidden Weights:
	-0.833278661909137	1.0158115952187496
	0.33273408761930334	-0.5978029738174121
		>50K		<=50K

Error sum for iteration 58900 = 56.50983798475408

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7353599889590334	-0.6845993493827982	age
Hidden Weights:
	-0.8332772634714306	1.0158101966981725
	0.33273037703743324	-0.5977992632282545
		>50K		<=50K

Error sum for iteration 59000 = 56.50983796995187

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7354527222171064	-0.6846617170179802	age
Hidden Weights:
	-0.8332758673729201	1.0158088005170216
	0.33272667065328554	-0.5977955568368473
		>50K		<=50K

Error sum for iteration 59100 = 56.509837955196346

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7355452996007442	-0.6847240132192127	age
Hidden Weights:
	-0.8332744736057619	1.0158074066674607
	0.33272296845728605	-0.597791854633601
		>50K		<=50K

Error sum for iteration 59200 = 56.50983794048708

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7356377216347157	-0.6847862381505774	age
Hidden Weights:
	-0.8332730821621357	1.015806015141638
	0.3327192704399025	-0.597788156608991
		>50K		<=50K

Error sum for iteration 59300 = 56.509837925824066

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7357299888412229	-0.6848483919755414	age
Hidden Weights:
	-0.8332716930342452	1.0158046259317808
	0.33271557659160866	-0.5977844627535207
		>50K		<=50K

Error sum for iteration 59400 = 56.50983791120687

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.735822101739814	-0.684910474856979	age
Hidden Weights:
	-0.8332703062143583	1.0158032390301632
	0.33271188690293735	-0.5977807730576613
		>50K		<=50K

Error sum for iteration 59500 = 56.509837896635446

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7359140608473859	-0.6849724869572678	age
Hidden Weights:
	-0.8332689216947643	1.0158018544290592
	0.33270820136440843	-0.5977770875119501
		>50K		<=50K

Error sum for iteration 59600 = 56.5098378821094

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7360058666783471	-0.6850344284381462	age
Hidden Weights:
	-0.8332675394678033	1.0158004721208194
	0.3327045199665952	-0.5977734061069773
		>50K		<=50K

Error sum for iteration 59700 = 56.50983786762881

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.73609751974444	-0.6850962994608659	age
Hidden Weights:
	-0.8332661595258389	1.0157990920977844
	0.33270084270011613	-0.5977697288333624
		>50K		<=50K

Error sum for iteration 59800 = 56.50983785319304

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7361890205548512	-0.6851581001861113	age
Hidden Weights:
	-0.8332647818612874	1.0157977143523862
	0.33269716955562345	-0.5977660556817314
		>50K		<=50K

Error sum for iteration 59900 = 56.50983783880221

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7362803696162489	-0.6852198307739663	age
Hidden Weights:
	-0.8332634064666032	1.01579633887708
	0.33269350052380625	-0.5977623866428222
		>50K		<=50K

Error sum for iteration 60000 = 56.509837824456085

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7363715674327108	-0.6852814913840647	age
Hidden Weights:
	-0.8332620333342677	1.0157949656643344
	0.3326898355953433	-0.5977587217073194
		>50K		<=50K

Error sum for iteration 60100 = 56.50983781015419

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7364626145058492	-0.6853430821754269	age
Hidden Weights:
	-0.8332606624568047	1.0157935947066807
	0.3326861747609942	-0.5977550608659686
		>50K		<=50K

Error sum for iteration 60200 = 56.5098377958967

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7365535113348189	-0.6854046033065458	age
Hidden Weights:
	-0.8332592938267712	1.0157922259966639
	0.33268251801153054	-0.5977514041095124
		>50K		<=50K

Error sum for iteration 60300 = 56.509837781683004

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7366442584161799	-0.6854660549353928	age
Hidden Weights:
	-0.8332579274367649	1.0157908595269123
	0.3326788653377436	-0.5977477514287592
		>50K		<=50K

Error sum for iteration 60400 = 56.509837767513105

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7367348562441537	-0.6855274372193794	age
Hidden Weights:
	-0.8332565632794318	1.0157894952900375
	0.3326752167304888	-0.5977441028145583
		>50K		<=50K

Error sum for iteration 60500 = 56.50983775338688

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7368253053104464	-0.6855887503153335	age
Hidden Weights:
	-0.8332552013474319	1.0157881332787082
	0.3326715721806163	-0.5977404582577962
		>50K		<=50K

Error sum for iteration 60600 = 56.509837739303975

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7369156061044021	-0.6856499943796586	age
Hidden Weights:
	-0.8332538416334742	1.0157867734856239
	0.3326679316790169	-0.5977368177492591
		>50K		<=50K

Error sum for iteration 60700 = 56.50983772526431

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7370057591129273	-0.6857111695681416	age
Hidden Weights:
	-0.8332524841302981	1.015785415903538
	0.3326642952166348	-0.5977331812799668
		>50K		<=50K

Error sum for iteration 60800 = 56.509837711267615

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7370957648204917	-0.6857722760360915	age
Hidden Weights:
	-0.8332511288306879	1.0157840605252213
	0.33266066278439704	-0.5977295488408854
		>50K		<=50K

Error sum for iteration 60900 = 56.509837697313515

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7371856237092261	-0.6858333139382665	age
Hidden Weights:
	-0.8332497757274492	1.0157827073434864
	0.3326570343733073	-0.5977259204229654
		>50K		<=50K

Error sum for iteration 61000 = 56.50983768340219

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7372753362588934	-0.6858942834289009	age
Hidden Weights:
	-0.8332484248134342	1.0157813563512035
	0.3326534099743736	-0.5977222960171596
		>50K		<=50K

Error sum for iteration 61100 = 56.50983766953312

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7373649029468645	-0.6859551846617238	age
Hidden Weights:
	-0.833247076081533	1.0157800075412329
	0.3326497895786833	-0.5977186756146371
		>50K		<=50K

Error sum for iteration 61200 = 56.50983765570619

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7374543242481609	-0.686016017789972	age
Hidden Weights:
	-0.833245729524657	1.015778660906508
	0.3326461731772675	-0.597715059206391
		>50K		<=50K

Error sum for iteration 61300 = 56.50983764192121

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7375436006356298	-0.6860767829663059	age
Hidden Weights:
	-0.8332443851357583	1.0157773164399635
	0.33264256076123094	-0.5977114467835419
		>50K		<=50K

Error sum for iteration 61400 = 56.50983762817818

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.737632732579589	-0.6861374803429111	age
Hidden Weights:
	-0.833243042907828	1.0157759741345929
	0.33263895232174284	-0.5977078383372583
		>50K		<=50K

Error sum for iteration 61500 = 56.509837614476595

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7377217205482103	-0.6861981100714729	age
Hidden Weights:
	-0.8332417028338848	1.0157746339834108
	0.33263534784995197	-0.5977042338587213
		>50K		<=50K

Error sum for iteration 61600 = 56.50983760081648

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7378105650074531	-0.6862586723030951	age
Hidden Weights:
	-0.8332403649069844	1.0157732959794752
	0.33263174733706546	-0.5977006333390655
		>50K		<=50K

Error sum for iteration 61700 = 56.50983758719764

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7378992664208538	-0.6863191671884588	age
Hidden Weights:
	-0.83323902912022	1.0157719601158886
	0.332628150774342	-0.5976970367695588
		>50K		<=50K

Error sum for iteration 61800 = 56.50983757361965

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7379878252497901	-0.6863795948776803	age
Hidden Weights:
	-0.8332376954667094	1.0157706263857476
	0.332624558153039	-0.5976934441414493
		>50K		<=50K

Error sum for iteration 61900 = 56.50983756008256

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7380762419533564	-0.6864399555203933	age
Hidden Weights:
	-0.83323636393961	1.015769294782226
	0.33262096946437225	-0.597689855446045
		>50K		<=50K

Error sum for iteration 62000 = 56.50983754658614

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7381645169885384	-0.6865002492657192	age
Hidden Weights:
	-0.8332350345321036	1.015767965298505
	0.332617384699656	-0.5976862706746068
		>50K		<=50K

Error sum for iteration 62100 = 56.50983753313003

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7382526508100037	-0.6865604762622897	age
Hidden Weights:
	-0.8332337072374174	1.0157666379278054
	0.33261380385028666	-0.5976826898185477
		>50K		<=50K

Error sum for iteration 62200 = 56.509837519714424

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7383406438703454	-0.6866206366583235	age
Hidden Weights:
	-0.8332323820488046	1.0157653126633606
	0.3326102269075866	-0.5976791128691833
		>50K		<=50K

Error sum for iteration 62300 = 56.509837506338734

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7384284966198816	-0.6866807306014655	age
Hidden Weights:
	-0.8332310589595494	1.0157639894984802
	0.3326066538629693	-0.5976755398179334
		>50K		<=50K

Error sum for iteration 62400 = 56.509837493003026

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7385162095068044	-0.6867407582389281	age
Hidden Weights:
	-0.8332297379629663	1.015762668426461
	0.33260308470788535	-0.5976719706562016
		>50K		<=50K

Error sum for iteration 62500 = 56.50983747970688

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7386037829771409	-0.686800719717319	age
Hidden Weights:
	-0.8332284190524104	1.0157613494406839
	0.33259951943378635	-0.5976684053755111
		>50K		<=50K

Error sum for iteration 62600 = 56.50983746645026

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7386912174747894	-0.6868606151827868	age
Hidden Weights:
	-0.833227102221262	1.0157600325344953
	0.3325959580321428	-0.5976648439672437
		>50K		<=50K

Error sum for iteration 62700 = 56.50983745323321

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.738778513441553	-0.6869204447810592	age
Hidden Weights:
	-0.8332257874629327	1.0157587177013299
	0.3325924004944768	-0.5976612864230032
		>50K		<=50K

Error sum for iteration 62800 = 56.50983744005523

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7388656713171408	-0.6869802086573822	age
Hidden Weights:
	-0.8332244747708688	1.0157574049346307
	0.3325888468123255	-0.5976577327342995
		>50K		<=50K

Error sum for iteration 62900 = 56.50983742691628

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7389526915391219	-0.6870399069564876	age
Hidden Weights:
	-0.8332231641385466	1.01575609422786
	0.3325852969772444	-0.5976541828927374
		>50K		<=50K

Error sum for iteration 63000 = 56.50983741381616

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7390395745430608	-0.6870995398226276	age
Hidden Weights:
	-0.8332218555594721	1.0157547855745237
	0.332581750980845	-0.5976506368898211
		>50K		<=50K

Error sum for iteration 63100 = 56.50983740075469

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7391263207623713	-0.6871591073995996	age
Hidden Weights:
	-0.8332205490271779	1.0157534789681655
	0.33257820881476935	-0.5976470947172247
		>50K		<=50K

Error sum for iteration 63200 = 56.50983738773169

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7392129306284576	-0.6872186098307042	age
Hidden Weights:
	-0.8332192445352314	1.0157521744023457
	0.33257467047064726	-0.5976435563665894
		>50K		<=50K

Error sum for iteration 63300 = 56.50983737474695

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7392994045706994	-0.6872780472588031	age
Hidden Weights:
	-0.8332179420772414	1.0157508718706654
	0.33257113594015586	-0.5976400218295981
		>50K		<=50K

Error sum for iteration 63400 = 56.50983736180039

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7393857430163588	-0.687337419826265	age
Hidden Weights:
	-0.8332166416468268	1.015749571366759
	0.33256760521497114	-0.5976364910978894
		>50K		<=50K

Error sum for iteration 63500 = 56.50983734889181

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7394719463908062	-0.6873967276749482	age
Hidden Weights:
	-0.8332153432376448	1.0157482728842693
	0.33256407828685064	-0.5976329641633119
		>50K		<=50K

Error sum for iteration 63600 = 56.50983733602097

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7395580151173241	-0.6874559709462766	age
Hidden Weights:
	-0.8332140468433827	1.0157469764169047
	0.33256055514757704	-0.5976294410175639
		>50K		<=50K

Error sum for iteration 63700 = 56.509837323187774

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7396439496172568	-0.6875151497812624	age
Hidden Weights:
	-0.8332127524577656	1.0157456819583683
	0.3325570357889197	-0.5976259216524394
		>50K		<=50K

Error sum for iteration 63800 = 56.509837310392015

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7397297503099267	-0.6875742643203959	age
Hidden Weights:
	-0.8332114600745503	1.0157443895023968
	0.3325535202026602	-0.5976224060597556
		>50K		<=50K

Error sum for iteration 63900 = 56.50983729763353

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7398154176127386	-0.6876333147037863	age
Hidden Weights:
	-0.8332101696874828	1.0157430990427814
	0.33255000838066745	-0.5976188942313456
		>50K		<=50K

Error sum for iteration 64000 = 56.50983728491215

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7399009519411396	-0.6876923010709859	age
Hidden Weights:
	-0.8332088812903914	1.0157418105733365
	0.33254650031482985	-0.5976153861591107
		>50K		<=50K

Error sum for iteration 64100 = 56.50983727222771

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7399863537085737	-0.6877512235611183	age
Hidden Weights:
	-0.8332075948771059	1.0157405240878625
	0.3325429959970347	-0.5976118818348987
		>50K		<=50K

Error sum for iteration 64200 = 56.50983725958016

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.740071623326591	-0.6878100823128922	age
Hidden Weights:
	-0.8332063104414857	1.0157392395802363
	0.33253949541917244	-0.597608381250655
		>50K		<=50K

Error sum for iteration 64300 = 56.50983724696925

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7401567612049129	-0.6878688774645221	age
Hidden Weights:
	-0.8332050279774195	1.0157379570443543
	0.3325359985732369	-0.5976048843983256
		>50K		<=50K

Error sum for iteration 64400 = 56.50983723439466

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7402417677512548	-0.687927609153752	age
Hidden Weights:
	-0.8332037474788332	1.0157366764741398
	0.33253250545117524	-0.5976013912699054
		>50K		<=50K

Error sum for iteration 64500 = 56.50983722185651

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7403266433714633	-0.6879862775180157	age
Hidden Weights:
	-0.8332024689396794	1.0157353978635284
	0.3325290160449864	-0.5975979018573431
		>50K		<=50K

Error sum for iteration 64600 = 56.50983720935455

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7404113884695168	-0.6880448826941719	age
Hidden Weights:
	-0.8332011923539232	1.0157341212064908
	0.33252553034667487	-0.5975944161526712
		>50K		<=50K

Error sum for iteration 64700 = 56.509837196888434

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7404960034474481	-0.6881034248185988	age
Hidden Weights:
	-0.8331999177155661	1.0157328464970459
	0.3325220483483115	-0.5975909341479501
		>50K		<=50K

Error sum for iteration 64800 = 56.509837184458284

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7405804887055695	-0.688161904027338	age
Hidden Weights:
	-0.8331986450186419	1.0157315737292056
	0.33251857004197266	-0.5975874558352481
		>50K		<=50K

Error sum for iteration 64900 = 56.50983717206371

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7406648446422361	-0.6882203204559533	age
Hidden Weights:
	-0.8331973742572226	1.0157303028970521
	0.33251509541974505	-0.5975839812066487
		>50K		<=50K

Error sum for iteration 65000 = 56.5098371597046

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7407490716540526	-0.6882786742395639	age
Hidden Weights:
	-0.8331961054253928	1.0157290339946707
	0.3325116244737384	-0.5975805102543421
		>50K		<=50K

Error sum for iteration 65100 = 56.50983714738092

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7408331701357854	-0.6883369655128774	age
Hidden Weights:
	-0.8331948385172416	1.0157277670161482
	0.332508157196132	-0.5975770429704633
		>50K		<=50K

Error sum for iteration 65200 = 56.50983713509241

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7409171404802859	-0.6883951944101204	age
Hidden Weights:
	-0.8331935735269261	1.0157265019556472
	0.33250469357909346	-0.5975735793471927
		>50K		<=50K

Error sum for iteration 65300 = 56.50983712283905

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7410009830786872	-0.6884533610651484	age
Hidden Weights:
	-0.8331923104486111	1.0157252388073157
	0.332501233614821	-0.5975701193766668
		>50K		<=50K

Error sum for iteration 65400 = 56.509837110620495

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7410846983203514	-0.6885114656113367	age
Hidden Weights:
	-0.8331910492764889	1.0157239775653397
	0.33249777729554686	-0.5975666630512173
		>50K		<=50K

Error sum for iteration 65500 = 56.509837098436755

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7411682865928074	-0.6885695081816093	age
Hidden Weights:
	-0.8331897900047827	1.0157227182239688
	0.33249432461350475	-0.5975632103630201
		>50K		<=50K

Error sum for iteration 65600 = 56.509837086287675

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7412517482818306	-0.688627488908578	age
Hidden Weights:
	-0.8331885326277428	1.0157214607774196
	0.3324908755609815	-0.5975597613043359
		>50K		<=50K

Error sum for iteration 65700 = 56.50983707417292

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7413350837714935	-0.6886854079242795	age
Hidden Weights:
	-0.8331872771396294	1.015720205219983
	0.33248743013029924	-0.5975563158674888
		>50K		<=50K

Error sum for iteration 65800 = 56.50983706209251

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7414182934440645	-0.6887432653603944	age
Hidden Weights:
	-0.8331860235347461	1.01571895154595
	0.3324839883137698	-0.5975528740448118
		>50K		<=50K

Error sum for iteration 65900 = 56.50983705004625

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7415013776800985	-0.6888010613482156	age
Hidden Weights:
	-0.8331847718074167	1.0157176997496364
	0.3324805501037331	-0.5975494358286612
		>50K		<=50K

Error sum for iteration 66000 = 56.50983703803392

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7415843368584237	-0.6888587960185434	age
Hidden Weights:
	-0.8331835219519932	1.0157164498254179
	0.33247711549258346	-0.5975460012113659
		>50K		<=50K

Error sum for iteration 66100 = 56.50983702605554

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7416671713561241	-0.6889164695018789	age
Hidden Weights:
	-0.8331822739628493	1.015715201767648
	0.33247368447270087	-0.5975425701853564
		>50K		<=50K

Error sum for iteration 66200 = 56.509837014110836

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7417498815485908	-0.6889740819281917	age
Hidden Weights:
	-0.8331810278343851	1.015713955570705
	0.3324702570365147	-0.5975391427430972
		>50K		<=50K

Error sum for iteration 66300 = 56.50983700219974

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7418324678095083	-0.6890316334270487	age
Hidden Weights:
	-0.8331797835610231	1.0157127112290427
	0.3324668331764777	-0.5975357188769843
		>50K		<=50K

Error sum for iteration 66400 = 56.509836990322015

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7419149305109735	-0.6890891241276786	age
Hidden Weights:
	-0.8331785411372242	1.0157114687371231
	0.3324634128850409	-0.5975322985794751
		>50K		<=50K

Error sum for iteration 66500 = 56.509836978477566

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7419972700232672	-0.689146554158798	age
Hidden Weights:
	-0.833177300557458	1.0157102280894117
	0.33245999615472066	-0.5975288818430218
		>50K		<=50K

Error sum for iteration 66600 = 56.50983696666634

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7420794867150752	-0.6892039236488265	age
Hidden Weights:
	-0.8331760618162286	1.0157089892803994
	0.33245658297801367	-0.5975254686602478
		>50K		<=50K

Error sum for iteration 66700 = 56.50983695488809

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.742161580953462	-0.6892612327256807	age
Hidden Weights:
	-0.8331748249080525	1.015707752304603
	0.33245317334746405	-0.5975220590236384
		>50K		<=50K

Error sum for iteration 66800 = 56.50983694314267

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7422435531038115	-0.6893184815169395	age
Hidden Weights:
	-0.8331735898274926	1.015706517156585
	0.33244976725565084	-0.5975186529258157
		>50K		<=50K

Error sum for iteration 66900 = 56.50983693142988

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7423254035298217	-0.6893756701497494	age
Hidden Weights:
	-0.8331723565691174	1.0157052838309166
	0.33244636469518063	-0.5975152503592303
		>50K		<=50K

Error sum for iteration 67000 = 56.50983691974976

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7424071325936105	-0.6894327987508193	age
Hidden Weights:
	-0.8331711251275249	1.0157040523221887
	0.3324429656586401	-0.5975118513166645
		>50K		<=50K

Error sum for iteration 67100 = 56.50983690810213

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7424887406557545	-0.6894898674465144	age
Hidden Weights:
	-0.8331698954973317	1.0157028226250386
	0.33243957013866793	-0.5975084557906791
		>50K		<=50K

Error sum for iteration 67200 = 56.50983689648676

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7425702280750891	-0.6895468763627488	age
Hidden Weights:
	-0.8331686676731864	1.0157015947341017
	0.3324361781279164	-0.5975050637739037
		>50K		<=50K

Error sum for iteration 67300 = 56.509836884903386

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7426515952089481	-0.6896038256250847	age
Hidden Weights:
	-0.833167441649767	1.0157003686440487
	0.33243278961908196	-0.5975016752590346
		>50K		<=50K

Error sum for iteration 67400 = 56.509836873352235

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7427328424130241	-0.6896607153587236	age
Hidden Weights:
	-0.8331662174217589	1.015699144349562
	0.33242940460486975	-0.5974982902388204
		>50K		<=50K

Error sum for iteration 67500 = 56.50983686183295

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7428139700414748	-0.6897175456883659	age
Hidden Weights:
	-0.833164994983881	1.0156979218453954
	0.3324260230779766	-0.5974949087059686
		>50K		<=50K

Error sum for iteration 67600 = 56.50983685034537

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7428949784468629	-0.6897743167383521	age
Hidden Weights:
	-0.8331637743308791	1.015696701126238
	0.33242264503117547	-0.5974915306532111
		>50K		<=50K

Error sum for iteration 67700 = 56.5098368388895

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.74297586798016	-0.6898310286327435	age
Hidden Weights:
	-0.8331625554575142	1.0156954821868729
	0.33241927045726455	-0.5974881560733198
		>50K		<=50K

Error sum for iteration 67800 = 56.509836827465016

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7430566389909077	-0.6898876814950138	age
Hidden Weights:
	-0.8331613383585623	1.0156942650220953
	0.33241589934902177	-0.5974847849590802
		>50K		<=50K

Error sum for iteration 67900 = 56.50983681607203

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7431372918270082	-0.6899442754484192	age
Hidden Weights:
	-0.8331601230288453	1.0156930496267111
	0.3324125316992426	-0.5974814173034079
		>50K		<=50K

Error sum for iteration 68000 = 56.509836804710076

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7432178268348114	-0.6900008106157771	age
Hidden Weights:
	-0.8331589094631902	1.015691835995553
	0.33240916750076255	-0.5974780530990822
		>50K		<=50K

Error sum for iteration 68100 = 56.509836793379364

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.743298244359217	-0.6900572871195254	age
Hidden Weights:
	-0.8331576976564573	1.0156906241234598
	0.33240580674646153	-0.5974746923389175
		>50K		<=50K

Error sum for iteration 68200 = 56.50983678207957

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7433785447435628	-0.6901137050817132	age
Hidden Weights:
	-0.8331564876035237	1.0156894140053314
	0.33240244942926583	-0.5974713350157993
		>50K		<=50K

Error sum for iteration 68300 = 56.50983677081065

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7434587283297165	-0.6901700646239778	age
Hidden Weights:
	-0.833155279299289	1.0156882056360597
	0.33239909554202884	-0.5974679811227295
		>50K		<=50K

Error sum for iteration 68400 = 56.50983675957238

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7435387954580253	-0.6902263658676034	age
Hidden Weights:
	-0.8331540727386721	1.0156869990105752
	0.332395745077668	-0.5974646306525762
		>50K		<=50K

Error sum for iteration 68500 = 56.50983674836485

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7436187464673358	-0.6902826089334761	age
Hidden Weights:
	-0.8331528679166178	1.0156857941237982
	0.33239239802917103	-0.5974612835982783
		>50K		<=50K

Error sum for iteration 68600 = 56.509836737187705

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7436985816949867	-0.6903387939421488	age
Hidden Weights:
	-0.8331516648280972	1.0156845909707062
	0.3323890543895073	-0.5974579399527704
		>50K		<=50K

Error sum for iteration 68700 = 56.509836726040845

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7437783014770123	-0.6903949210138017	age
Hidden Weights:
	-0.8331504634680817	1.015683389546291
	0.33238571415166535	-0.5974545997091275
		>50K		<=50K

Error sum for iteration 68800 = 56.50983671492424

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7438579061478368	-0.6904509902681834	age
Hidden Weights:
	-0.8331492638315983	1.0156821898455575
	0.3323823773086537	-0.5974512628603421
		>50K		<=50K

Error sum for iteration 68900 = 56.50983670383764

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7439373960403869	-0.690507001824728	age
Hidden Weights:
	-0.8331480659136743	1.0156809918635248
	0.33237904385350303	-0.597447929399414
		>50K		<=50K

Error sum for iteration 69000 = 56.50983669278117

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7440167714862975	-0.690562955802471	age
Hidden Weights:
	-0.8331468697093632	1.0156797955952617
	0.33237571377929553	-0.5974445993193872
		>50K		<=50K

Error sum for iteration 69100 = 56.5098366817543

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.74409603281569	-0.6906188523200639	age
Hidden Weights:
	-0.8331456752137382	1.0156786010358436
	0.33237238707910277	-0.5974412726133422
		>50K		<=50K

Error sum for iteration 69200 = 56.509836670757416

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7441751803572227	-0.6906746914958599	age
Hidden Weights:
	-0.8331444824218964	1.0156774081803541
	0.3323690637459966	-0.5974379492744573
		>50K		<=50K

Error sum for iteration 69300 = 56.50983665978986

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7442542144381561	-0.6907304734477356	age
Hidden Weights:
	-0.833143291328961	1.015676217023918
	0.3323657437731209	-0.5974346292958572
		>50K		<=50K

Error sum for iteration 69400 = 56.50983664885196

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.744333135384353	-0.6907861982932783	age
Hidden Weights:
	-0.8331421019300576	1.015675027561672
	0.33236242715362363	-0.5974313126706066
		>50K		<=50K

Error sum for iteration 69500 = 56.509836637943266

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7444119435203369	-0.6908418661496759	age
Hidden Weights:
	-0.8331409142203479	1.0156738397887555
	0.33235911388068856	-0.5974279993919002
		>50K		<=50K

Error sum for iteration 69600 = 56.50983662706387

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7444906391691436	-0.6908974771338017	age
Hidden Weights:
	-0.8331397281950198	1.0156726537003866
	0.33235580394749625	-0.5974246894529531
		>50K		<=50K

Error sum for iteration 69700 = 56.50983661621356

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7445692226524218	-0.6909530313621399	age
Hidden Weights:
	-0.8331385438492689	1.0156714692917337
	0.3323524973472299	-0.5974213828469619
		>50K		<=50K

Error sum for iteration 69800 = 56.509836605392124

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7446476942905125	-0.6910085289508464	age
Hidden Weights:
	-0.833137361178316	1.0156702865580403
	0.332349194073133	-0.5974180795671289
		>50K		<=50K

Error sum for iteration 69900 = 56.50983659459981

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.74472605440228	-0.6910639700156785	age
Hidden Weights:
	-0.8331361801774008	1.0156691054945102
	0.33234589411844034	-0.5974147796066924
		>50K		<=50K

Error sum for iteration 70000 = 56.50983658383607

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7448043033053049	-0.6911193546721083	age
Hidden Weights:
	-0.8331350008417814	1.0156679260964412
	0.33234259747639655	-0.5974114829589923
		>50K		<=50K

Error sum for iteration 70100 = 56.509836573101026

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7448824413157717	-0.6911746830351814	age
Hidden Weights:
	-0.8331338231667405	1.0156667483591082
	0.3323393041403392	-0.5974081896172696
		>50K		<=50K

Error sum for iteration 70200 = 56.509836562394476

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7449604687485815	-0.691229955219648	age
Hidden Weights:
	-0.8331326471475861	1.015665572277789
	0.33233601410357205	-0.5974048995747905
		>50K		<=50K

Error sum for iteration 70300 = 56.50983655171646

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7450383859172363	-0.6912851713398044	age
Hidden Weights:
	-0.8331314727796375	1.0156643978478208
	0.33233272735942	-0.597401612824934
		>50K		<=50K

Error sum for iteration 70400 = 56.50983654106641

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7451161931339649	-0.6913403315097372	age
Hidden Weights:
	-0.8331303000582364	1.015663225064558
	0.33232944390123076	-0.5973983293610864
		>50K		<=50K

Error sum for iteration 70500 = 56.50983653044495

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.745193890709549	-0.6913954358430033	age
Hidden Weights:
	-0.83312912897874	1.0156620539233356
	0.33232616372238655	-0.5973950491766129
		>50K		<=50K

Error sum for iteration 70600 = 56.5098365198514

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.745271478953588	-0.6914504844530194	age
Hidden Weights:
	-0.8331279595365343	1.0156608844195532
	0.3323228868162653	-0.5973917722648676
		>50K		<=50K

Error sum for iteration 70700 = 56.50983650928559

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7453489581742487	-0.6915054774527314	age
Hidden Weights:
	-0.833126791727013	1.015659716548596
	0.3323196131762757	-0.5973884986192195
		>50K		<=50K

Error sum for iteration 70800 = 56.50983649874787

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7454263286785177	-0.6915604149547931	age
Hidden Weights:
	-0.8331256255456038	1.0156585503058853
	0.33231634279586486	-0.5973852282331636
		>50K		<=50K

Error sum for iteration 70900 = 56.509836488237745

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7455035907719836	-0.6916152970714713	age
Hidden Weights:
	-0.8331244609877436	1.0156573856868687
	0.33231307566846274	-0.597381961100101
		>50K		<=50K

Error sum for iteration 71000 = 56.50983647775537

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7455807447589955	-0.6916701239147406	age
Hidden Weights:
	-0.8331232980488882	1.0156562226870076
	0.3323098117875611	-0.5973786972135257
		>50K		<=50K

Error sum for iteration 71100 = 56.50983646730032

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.745657790942639	-0.69172489559622	age
Hidden Weights:
	-0.8331221367245154	1.0156550613017834
	0.33230655114664953	-0.59737543656694
		>50K		<=50K

Error sum for iteration 71200 = 56.5098364568727

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7457347296246873	-0.6917796122271496	age
Hidden Weights:
	-0.8331209770101193	1.0156539015266794
	0.33230329373920314	-0.5973721791539106
		>50K		<=50K

Error sum for iteration 71300 = 56.509836446472534

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7458115611056578	-0.6918342739184995	age
Hidden Weights:
	-0.8331198189012239	1.0156527433571982
	0.3323000395587715	-0.5973689249679925
		>50K		<=50K

Error sum for iteration 71400 = 56.50983643609937

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7458882856848258	-0.6918888807808392	age
Hidden Weights:
	-0.8331186623933526	1.0156515867888911
	0.3322967885988865	-0.5973656740026503
		>50K		<=50K

Error sum for iteration 71500 = 56.50983642575339

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7459649036601868	-0.691943432924428	age
Hidden Weights:
	-0.8331175074820566	1.0156504318173
	0.33229354085313556	-0.5973624262514381
		>50K		<=50K

Error sum for iteration 71600 = 56.509836415434286

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7460414153284928	-0.6919979304591748	age
Hidden Weights:
	-0.8331163541629247	1.0156492784380056
	0.3322902963151018	-0.5973591817079105
		>50K		<=50K

Error sum for iteration 71700 = 56.50983640514203

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7461178209852722	-0.6920523734947353	age
Hidden Weights:
	-0.8331152024315326	1.01564812664659
	0.3322870549783904	-0.5973559403657688
		>50K		<=50K

Error sum for iteration 71800 = 56.5098363948766

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7461941209248143	-0.6921067621403946	age
Hidden Weights:
	-0.8331140522834891	1.0156469764386706
	0.33228381683662217	-0.5973527022185736
		>50K		<=50K

Error sum for iteration 71900 = 56.50983638463771

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7462703154401471	-0.6921610965050649	age
Hidden Weights:
	-0.8331129037144276	1.0156458278098577
	0.33228058188345627	-0.5973494672599432
		>50K		<=50K

Error sum for iteration 72000 = 56.50983637442543

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7463464048231575	-0.6922153766973738	age
Hidden Weights:
	-0.8331117567199778	1.015644680755796
	0.33227735011256215	-0.5973462354835758
		>50K		<=50K

Error sum for iteration 72100 = 56.50983636423956

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.746422389364462	-0.6922696028256554	age
Hidden Weights:
	-0.8331106112958121	1.0156435352721616
	0.3322741215176083	-0.5973430068831767
		>50K		<=50K

Error sum for iteration 72200 = 56.50983635408004

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7464982693535245	-0.6923237749978116	age
Hidden Weights:
	-0.8331094674376077	1.0156423913546222
	0.33227089609228694	-0.5973397814524734
		>50K		<=50K

Error sum for iteration 72300 = 56.50983634394672

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7465740450785552	-0.6923778933215089	age
Hidden Weights:
	-0.8331083251410641	1.0156412489988824
	0.3322676738303536	-0.5973365591850996
		>50K		<=50K

Error sum for iteration 72400 = 56.50983633383947

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7466497168265877	-0.692431957904089	age
Hidden Weights:
	-0.8331071844019025	1.0156401082006514
	0.33226445472551064	-0.5973333400748632
		>50K		<=50K

Error sum for iteration 72500 = 56.5098363237583

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7467252848834574	-0.6924859688524695	age
Hidden Weights:
	-0.8331060452158493	1.015638968955675
	0.33226123877154573	-0.5973301241154674
		>50K		<=50K

Error sum for iteration 72600 = 56.50983631370291

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7468007495338885	-0.6925399262734022	age
Hidden Weights:
	-0.8331049075786544	1.0156378312596848
	0.33225802596222154	-0.5973269113007349
		>50K		<=50K

Error sum for iteration 72700 = 56.50983630367365

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.746876111061372	-0.6925938302732187	age
Hidden Weights:
	-0.8331037714860885	1.0156366951084583
	0.33225481629134596	-0.5973237016244743
		>50K		<=50K

Error sum for iteration 72800 = 56.509836293669885

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7469513697482358	-0.6926476809579938	age
Hidden Weights:
	-0.8331026369339348	1.0156355604977707
	0.3322516097527225	-0.5973204950804538
		>50K		<=50K

Error sum for iteration 72900 = 56.50983628369171

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7470265258756705	-0.692701478433399	age
Hidden Weights:
	-0.8331015039180032	1.0156344274234463
	0.3322484063401714	-0.597317291662526
		>50K		<=50K

Error sum for iteration 73000 = 56.5098362737391

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.747101579723673	-0.6927552228048931	age
Hidden Weights:
	-0.8331003724341104	1.0156332958812966
	0.3322452060475544	-0.5973140913645079
		>50K		<=50K

Error sum for iteration 73100 = 56.50983626381196

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7471765315711755	-0.6928089141775305	age
Hidden Weights:
	-0.8330992424780912	1.0156321658671519
	0.3322420088687367	-0.5973108941803401
		>50K		<=50K

Error sum for iteration 73200 = 56.50983625391007

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7472513816958708	-0.692862552656126	age
Hidden Weights:
	-0.833098114045806	1.0156310373768782
	0.33223881479759854	-0.597307700103875
		>50K		<=50K

Error sum for iteration 73300 = 56.5098362440333

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7473261303743827	-0.6929161383451461	age
Hidden Weights:
	-0.8330969871331221	1.015629910406338
	0.33223562382803773	-0.5973045091289945
		>50K		<=50K

Error sum for iteration 73400 = 56.50983623418188

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7474007778821524	-0.6929696713487885	age
Hidden Weights:
	-0.8330958617359259	1.0156287849514072
	0.33223243595400104	-0.5973013212496334
		>50K		<=50K

Error sum for iteration 73500 = 56.50983622435529

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7474753244935899	-0.6930231517709242	age
Hidden Weights:
	-0.8330947378501212	1.0156276610080055
	0.3322292511694474	-0.5972981364597253
		>50K		<=50K

Error sum for iteration 73600 = 56.50983621455369

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.747549770481866	-0.6930765797150495	age
Hidden Weights:
	-0.8330936154716335	1.0156265385720467
	0.33222606946829436	-0.5972949547532722
		>50K		<=50K

Error sum for iteration 73700 = 56.50983620477694

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7476241161191763	-0.6931299552844378	age
Hidden Weights:
	-0.8330924945964029	1.0156254176394797
	0.3322228908445398	-0.5972917761242079
		>50K		<=50K

Error sum for iteration 73800 = 56.50983619502489

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7476983616765297	-0.6931832785819889	age
Hidden Weights:
	-0.8330913752203768	1.0156242982062424
	0.33221971529216154	-0.5972886005665614
		>50K		<=50K

Error sum for iteration 73900 = 56.50983618529748

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7477725074238567	-0.6932365497104102	age
Hidden Weights:
	-0.8330902573395305	1.01562318026831
	0.3322165428051639	-0.5972854280743083
		>50K		<=50K

Error sum for iteration 74000 = 56.50983617559453

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.747846553629987	-0.6932897687719931	age
Hidden Weights:
	-0.8330891409498521	1.0156220638216706
	0.33221337337758783	-0.5972822586414485
		>50K		<=50K

Error sum for iteration 74100 = 56.509836165916184

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7479205005626787	-0.6933429358687637	age
Hidden Weights:
	-0.8330880260473321	1.0156209488623218
	0.33221020700347387	-0.5972790922621208
		>50K		<=50K

Error sum for iteration 74200 = 56.50983615626219

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7479943484885885	-0.693396051102445	age
Hidden Weights:
	-0.8330869126280102	1.0156198353862906
	0.332207043676912	-0.5972759289303278
		>50K		<=50K

Error sum for iteration 74300 = 56.50983614663235

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7480680976732913	-0.6934491145745403	age
Hidden Weights:
	-0.8330858006879088	1.0156187233896108
	0.332203883391943	-0.5972727686401598
		>50K		<=50K

Error sum for iteration 74400 = 56.50983613702671

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7481417483813522	-0.6935021263861658	age
Hidden Weights:
	-0.83308469022308	1.0156176128683287
	0.33220072614268903	-0.5972696113857325
		>50K		<=50K

Error sum for iteration 74500 = 56.50983612744506

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7482153008762134	-0.6935550866381067	age
Hidden Weights:
	-0.8330835812295869	1.0156165038185239
	0.33219757192326504	-0.5972664571611184
		>50K		<=50K

Error sum for iteration 74600 = 56.5098361178875

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7482887554202653	-0.6936079954309403	age
Hidden Weights:
	-0.8330824737035275	1.0156153962362564
	0.33219442072779254	-0.5972633059604573
		>50K		<=50K

Error sum for iteration 74700 = 56.50983610835379

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7483621122748894	-0.6936608528649532	age
Hidden Weights:
	-0.8330813676409838	1.0156142901176315
	0.3321912725504541	-0.597260157777876
		>50K		<=50K

Error sum for iteration 74800 = 56.509836098843984

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7484353717004455	-0.6937136590400682	age
Hidden Weights:
	-0.833080263038074	1.0156131854587798
	0.33218812738537223	-0.5972570126075926
		>50K		<=50K

Error sum for iteration 74900 = 56.50983608935771

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7485085339561098	-0.6937664140559751	age
Hidden Weights:
	-0.8330791598909277	1.0156120822558155
	0.3321849852267333	-0.5972538704438437
		>50K		<=50K

Error sum for iteration 75000 = 56.509836079895294

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7485815993001623	-0.6938191180120113	age
Hidden Weights:
	-0.8330780581956962	1.0156109805048656
	0.3321818460687517	-0.597250731280758
		>50K		<=50K

Error sum for iteration 75100 = 56.50983607045627

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7486545679898197	-0.6938717710072699	age
Hidden Weights:
	-0.8330769579485232	1.0156098802021203
	0.33217870990563914	-0.5972475951125166
		>50K		<=50K

Error sum for iteration 75200 = 56.50983606104069

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7487274402812373	-0.6939243731406096	age
Hidden Weights:
	-0.8330758591456038	1.015608781343753
	0.3321755767316625	-0.5972444619333606
		>50K		<=50K

Error sum for iteration 75300 = 56.50983605164845

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7488002164295845	-0.6939769245104388	age
Hidden Weights:
	-0.8330747617831158	1.0156076839259358
	0.33217244654108297	-0.5972413317375685
		>50K		<=50K

Error sum for iteration 75400 = 56.50983604227955

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7488728966890017	-0.6940294252150678	age
Hidden Weights:
	-0.8330736658572736	1.0156065879448724
	0.33216931932811466	-0.5972382045194704
		>50K		<=50K

Error sum for iteration 75500 = 56.509836032933784

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7489454813126643	-0.694081875352345	age
Hidden Weights:
	-0.8330725713642956	1.015605493396785
	0.3321661950870601	-0.5972350802732592
		>50K		<=50K

Error sum for iteration 75600 = 56.50983602361107

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7490179705526694	-0.6941342750199904	age
Hidden Weights:
	-0.8330714783004078	1.0156044002779305
	0.3321630738122066	-0.597231958993297
		>50K		<=50K

Error sum for iteration 75700 = 56.509836014311404

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7490903646601684	-0.6941866243152867	age
Hidden Weights:
	-0.8330703866618724	1.0156033085845508
	0.3321599554979064	-0.5972288406738473
		>50K		<=50K

Error sum for iteration 75800 = 56.50983600503458

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7491626638853338	-0.6942389233354379	age
Hidden Weights:
	-0.8330692964449444	1.0156022183129152
	0.33215684013848074	-0.5972257253092687
		>50K		<=50K

Error sum for iteration 75900 = 56.509835995780655

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7492348684773212	-0.6942911721772042	age
Hidden Weights:
	-0.8330682076459144	1.0156011294592662
	0.3321537277282365	-0.5972226128939521
		>50K		<=50K

Error sum for iteration 76000 = 56.50983598654946

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7493069786842929	-0.6943433709371306	age
Hidden Weights:
	-0.833067120261068	1.0156000420199207
	0.3321506182615772	-0.5972195034222545
		>50K		<=50K

Error sum for iteration 76100 = 56.509835977340956

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7493789947535121	-0.6943955197115028	age
Hidden Weights:
	-0.8330660342867204	1.015598955991211
	0.3321475117328926	-0.5972163968885038
		>50K		<=50K

Error sum for iteration 76200 = 56.50983596815491

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7494509169311642	-0.6944476185962399	age
Hidden Weights:
	-0.8330649497191951	1.015597871369421
	0.33214440813655877	-0.597213293287062
		>50K		<=50K

Error sum for iteration 76300 = 56.50983595899157

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7495227454625091	-0.6944996676870312	age
Hidden Weights:
	-0.833063866554819	1.0155967881509134
	0.3321413074670325	-0.5972101926124184
		>50K		<=50K

Error sum for iteration 76400 = 56.509835949850526

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7495944805919239	-0.6945516670792752	age
Hidden Weights:
	-0.8330627847899544	1.0155957063320395
	0.3321382097187107	-0.5972070948589809
		>50K		<=50K

Error sum for iteration 76500 = 56.509835940731676

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.749666122562742	-0.6946036168681696	age
Hidden Weights:
	-0.8330617044209638	1.0155946259091515
	0.33213511488600767	-0.597204000021224
		>50K		<=50K

Error sum for iteration 76600 = 56.50983593163522

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7497376716173478	-0.6946555171485583	age
Hidden Weights:
	-0.8330606254442319	1.0155935468786395
	0.3321320229634332	-0.5972009080935959
		>50K		<=50K

Error sum for iteration 76700 = 56.509835922560995

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7498091279972257	-0.6947073680150697	age
Hidden Weights:
	-0.8330595478561489	1.015592469236885
	0.3321289339454371	-0.5971978190705607
		>50K		<=50K

Error sum for iteration 76800 = 56.50983591350863

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7498804919428407	-0.6947591695619776	age
Hidden Weights:
	-0.8330584716531283	1.0155913929803233
	0.33212584782652704	-0.5971947329466395
		>50K		<=50K

Error sum for iteration 76900 = 56.50983590447846

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7499517636938293	-0.6948109218833433	age
Hidden Weights:
	-0.8330573968315832	1.0155903181053585
	0.3321227646012274	-0.597191649716307
		>50K		<=50K

Error sum for iteration 77000 = 56.50983589547021

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7500229434888136	-0.6948626250730243	age
Hidden Weights:
	-0.8330563233879577	1.0155892446084063
	0.332119684264031	-0.5971885693741513
		>50K		<=50K

Error sum for iteration 77100 = 56.509835886483515

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7500940315654987	-0.694914279224533	age
Hidden Weights:
	-0.8330552513186988	1.0155881724859568
	0.3321166068094858	-0.5971854919146691
		>50K		<=50K

Error sum for iteration 77200 = 56.50983587751885

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7501650281607183	-0.6949658844310879	age
Hidden Weights:
	-0.833054180620282	1.0155871017344411
	0.3321135322321709	-0.5971824173323863
		>50K		<=50K

Error sum for iteration 77300 = 56.509835868575834

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7502359335103232	-0.6950174407856878	age
Hidden Weights:
	-0.8330531112891708	1.0155860323503478
	0.3321104605266591	-0.5971793456219153
		>50K		<=50K

Error sum for iteration 77400 = 56.50983585965434

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7503067478493115	-0.6950689483810106	age
Hidden Weights:
	-0.8330520433218653	1.0155849643301798
	0.3321073916875292	-0.5971762767778017
		>50K		<=50K

Error sum for iteration 77500 = 56.509835850754314

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7503774714117665	-0.695120407309602	age
Hidden Weights:
	-0.8330509767148616	1.0155838976704397
	0.3321043257093823	-0.5971732107946591
		>50K		<=50K

Error sum for iteration 77600 = 56.509835841875876

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7504481044307971	-0.6951718176636051	age
Hidden Weights:
	-0.8330499114646794	1.0155828323676235
	0.33210126258683614	-0.5971701476671664
		>50K		<=50K

Error sum for iteration 77700 = 56.50983583301856

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.750518647138672	-0.6952231795350166	age
Hidden Weights:
	-0.8330488475678569	1.015581768418289
	0.33209820231452397	-0.5971670873898948
		>50K		<=50K

Error sum for iteration 77800 = 56.509835824182694

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7505890997667201	-0.6952744930154451	age
Hidden Weights:
	-0.8330477850209373	1.0155807058189716
	0.33209514488708647	-0.5971640299574843
		>50K		<=50K

Error sum for iteration 77900 = 56.50983581536803

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7506594625454978	-0.695325758196325	age
Hidden Weights:
	-0.8330467238204764	1.0155796445662286
	0.33209209029919207	-0.5971609753646343
		>50K		<=50K

Error sum for iteration 78000 = 56.50983580657432

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7507297357045472	-0.6953769751688466	age
Hidden Weights:
	-0.8330456639630505	1.0155785846566168
	0.33208903854551747	-0.5971579236060013
		>50K		<=50K

Error sum for iteration 78100 = 56.50983579780196

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7507999194726176	-0.6954281440238541	age
Hidden Weights:
	-0.8330446054452361	1.01557752608674
	0.3320859896207525	-0.5971548746762986
		>50K		<=50K

Error sum for iteration 78200 = 56.509835789050264

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7508700140775779	-0.6954792648519644	age
Hidden Weights:
	-0.8330435482636362	1.0155764688531876
	0.33208294351959433	-0.5971518285703015
		>50K		<=50K

Error sum for iteration 78300 = 56.50983578031965

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7509400197463281	-0.6955303377435865	age
Hidden Weights:
	-0.8330424924148607	1.0155754129525603
	0.3320799002367748	-0.5971487852826414
		>50K		<=50K

Error sum for iteration 78400 = 56.50983577160984

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7510099367050107	-0.6955813627888756	age
Hidden Weights:
	-0.8330414378955363	1.0155743583814818
	0.33207685976704665	-0.5971457448080715
		>50K		<=50K

Error sum for iteration 78500 = 56.509835762920645

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7510797651788417	-0.695632340077734	age
Hidden Weights:
	-0.8330403847022914	1.0155733051366107
	0.33207382210514724	-0.5971427071413392
		>50K		<=50K

Error sum for iteration 78600 = 56.50983575425224

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.751149505392205	-0.6956832696997164	age
Hidden Weights:
	-0.8330393328317771	1.0155722532145788
	0.3320707872458395	-0.597139672277183
		>50K		<=50K

Error sum for iteration 78700 = 56.509835745604285

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7512191575686158	-0.6957341517441964	age
Hidden Weights:
	-0.8330382822806679	1.0155712026120494
	0.3320677551839108	-0.5971366402104594
		>50K		<=50K

Error sum for iteration 78800 = 56.50983573697699

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7512887219307846	-0.6957849863003007	age
Hidden Weights:
	-0.833037233045611	1.0155701533256964
	0.3320647259141594	-0.5971336109359188
		>50K		<=50K

Error sum for iteration 78900 = 56.50983572837005

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7513581987005475	-0.6958357734568519	age
Hidden Weights:
	-0.8330361851233163	1.0155691053522096
	0.33206169943139596	-0.5971305844483961
		>50K		<=50K

Error sum for iteration 79000 = 56.5098357197836

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7514275880989415	-0.6958865133025485	age
Hidden Weights:
	-0.8330351385104653	1.015568058688276
	0.3320586757304417	-0.5971275607427091
		>50K		<=50K

Error sum for iteration 79100 = 56.50983571121728

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7514968903460623	-0.6959372059256685	age
Hidden Weights:
	-0.8330340932037869	1.0155670133306105
	0.33205565480614163	-0.597124539813688
		>50K		<=50K

Error sum for iteration 79200 = 56.50983570267126

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7515661056612826	-0.6959878514143476	age
Hidden Weights:
	-0.8330330492000009	1.015565969275963
	0.3320526366533525	-0.5971215216561859
		>50K		<=50K

Error sum for iteration 79300 = 56.50983569414556

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7516352342630658	-0.6960384498565146	age
Hidden Weights:
	-0.8330320064958363	1.0155649265210407
	0.3320496212669443	-0.5971185062650815
		>50K		<=50K

Error sum for iteration 79400 = 56.5098356856396

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7517042763691004	-0.6960890013397663	age
Hidden Weights:
	-0.8330309650880563	1.0155638850626092
	0.332046608641818	-0.5971154936352399
		>50K		<=50K

Error sum for iteration 79500 = 56.50983567715391

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7517732321962203	-0.6961395059514921	age
Hidden Weights:
	-0.8330299249734139	1.0155628448974108
	0.33204359877284434	-0.5971124837615669
		>50K		<=50K

Error sum for iteration 79600 = 56.50983566868811

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7518421019604657	-0.6961899637788307	age
Hidden Weights:
	-0.8330288861486729	1.0155618060222376
	0.33204059165492905	-0.5971094766389594
		>50K		<=50K

Error sum for iteration 79700 = 56.50983566024211

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7519108858770545	-0.6962403749086907	age
Hidden Weights:
	-0.8330278486106303	1.0155607684338646
	0.332037587283021	-0.5971064722623428
		>50K		<=50K

Error sum for iteration 79800 = 56.50983565181592

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7519795841604645	-0.6962907394276875	age
Hidden Weights:
	-0.833026812356082	1.0155597321290797
	0.33203458565203536	-0.5971034706266596
		>50K		<=50K

Error sum for iteration 79900 = 56.509835643409474

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7520481970242815	-0.6963410574221686	age
Hidden Weights:
	-0.8330257773818355	1.0155586971047144
	0.3320315867569643	-0.5971004717268467
		>50K		<=50K

Error sum for iteration 80000 = 56.50983563502264

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7521167246813345	-0.6963913289784487	age
Hidden Weights:
	-0.833024743684717	1.015557663357572
	0.33202859059275586	-0.5970974755579226
		>50K		<=50K

Error sum for iteration 80100 = 56.50983562665548

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.752185167343621	-0.6964415541823651	age
Hidden Weights:
	-0.8330237112615568	1.0155566308844983
	0.33202559715439156	-0.5970944821148748
		>50K		<=50K

Error sum for iteration 80200 = 56.509835618307605

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7522535252223724	-0.6964917331196704	age
Hidden Weights:
	-0.8330226801091953	1.015555599682326
	0.33202260643688347	-0.5970914913926696
		>50K		<=50K

Error sum for iteration 80300 = 56.509835609979454

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7523217985280577	-0.6965418658757893	age
Hidden Weights:
	-0.8330216502244896	1.0155545697479125
	0.3320196184352165	-0.5970885033863172
		>50K		<=50K

Error sum for iteration 80400 = 56.509835601670524

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7523899874703517	-0.6965919525359546	age
Hidden Weights:
	-0.8330206216043053	1.015553541078136
	0.3320166331444233	-0.5970855180908835
		>50K		<=50K

Error sum for iteration 80500 = 56.509835593380906

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7524580922580769	-0.6966419931851141	age
Hidden Weights:
	-0.8330195942455422	1.0155525136698709
	0.3320136505595496	-0.5970825355013704
		>50K		<=50K

Error sum for iteration 80600 = 56.50983558511065

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7525261130993383	-0.6966919879080303	age
Hidden Weights:
	-0.8330185681450711	1.0155514875199976
	0.33201067067562384	-0.5970795556128533
		>50K		<=50K

Error sum for iteration 80700 = 56.50983557685945

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7525940502014905	-0.6967419367892478	age
Hidden Weights:
	-0.8330175432998069	1.0155504626254361
	0.3320076934877124	-0.5970765784203377
		>50K		<=50K

Error sum for iteration 80800 = 56.50983556862736

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7526619037711124	-0.696791839912991	age
Hidden Weights:
	-0.833016519706653	1.0155494389830948
	0.3320047189908989	-0.5970736039189084
		>50K		<=50K

Error sum for iteration 80900 = 56.50983556041432

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7527296740139968	-0.6968416973633123	age
Hidden Weights:
	-0.8330154973625435	1.0155484165898876
	0.3320017471802483	-0.5970706321036756
		>50K		<=50K

Error sum for iteration 81000 = 56.509835552220125

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.752797361135189	-0.696891509224039	age
Hidden Weights:
	-0.8330144762644166	1.0155473954427716
	0.33199877805091427	-0.5970676629697168
		>50K		<=50K

Error sum for iteration 81100 = 56.509835544045096

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.752864965338987	-0.6969412755788026	age
Hidden Weights:
	-0.8330134564092166	1.0155463755386787
	0.33199581159799985	-0.5970646965121885
		>50K		<=50K

Error sum for iteration 81200 = 56.50983553588867

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7529324868289069	-0.6969909965109182	age
Hidden Weights:
	-0.8330124377938967	1.0155453568745771
	0.3319928478166131	-0.5970617327262192
		>50K		<=50K

Error sum for iteration 81300 = 56.50983552775114

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7529999258077036	-0.6970406721035561	age
Hidden Weights:
	-0.8330114204154405	1.0155443394474324
	0.33198988670192686	-0.5970587716069311
		>50K		<=50K

Error sum for iteration 81400 = 56.50983551963218

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7530672824775088	-0.6970903024395466	age
Hidden Weights:
	-0.8330104042708302	1.0155433232542173
	0.33198692824909387	-0.5970558131495102
		>50K		<=50K

Error sum for iteration 81500 = 56.50983551153197

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.753134557039559	-0.6971398876016185	age
Hidden Weights:
	-0.8330093893570502	1.0155423082919475
	0.33198397245328115	-0.5970528573491078
		>50K		<=50K

Error sum for iteration 81600 = 56.509835503450276

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7532017496943724	-0.6971894276721422	age
Hidden Weights:
	-0.8330083756711024	1.0155412945576172
	0.3319810193096865	-0.5970499042009013
		>50K		<=50K

Error sum for iteration 81700 = 56.50983549538724

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.753268860641827	-0.6972389227333943	age
Hidden Weights:
	-0.8330073632100055	1.0155402820482438
	0.33197806881348735	-0.5970469537001228
		>50K		<=50K

Error sum for iteration 81800 = 56.509835487342414

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.753335890080941	-0.6972883728674055	age
Hidden Weights:
	-0.8330063519707815	1.01553927076084
	0.3319751209599054	-0.5970440058419628
		>50K		<=50K

Error sum for iteration 81900 = 56.50983547931612

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7534028382101001	-0.697337778155892	age
Hidden Weights:
	-0.8330053419504752	1.0155382606924357
	0.3319721757441545	-0.5970410606216345
		>50K		<=50K

Error sum for iteration 82000 = 56.509835471308186

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7534697052270101	-0.6973871386803492	age
Hidden Weights:
	-0.8330043331461345	1.0155372518400962
	0.3319692331614678	-0.5970381180343904
		>50K		<=50K

Error sum for iteration 82100 = 56.5098354633183

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7535364913285505	-0.6974364545221543	age
Hidden Weights:
	-0.8330033255548188	1.0155362442008817
	0.3319662932070833	-0.5970351780754286
		>50K		<=50K

Error sum for iteration 82200 = 56.50983545534673

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7536031967108832	-0.6974857257624012	age
Hidden Weights:
	-0.8330023191735874	1.0155352377718514
	0.33196335587628295	-0.5970322407400389
		>50K		<=50K

Error sum for iteration 82300 = 56.50983544739336

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7536698215695313	-0.6975349524819938	age
Hidden Weights:
	-0.8330013139995269	1.015534232550091
	0.331960421164353	-0.597029306023608
		>50K		<=50K

Error sum for iteration 82400 = 56.50983543945786

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7537363660993296	-0.6975841347615986	age
Hidden Weights:
	-0.8330003100297226	1.0155332285326937
	0.33195748906656053	-0.5970263739213032
		>50K		<=50K

Error sum for iteration 82500 = 56.50983543154058

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7538028304942631	-0.6976332726816179	age
Hidden Weights:
	-0.8329993072612712	1.0155322257167372
	0.3319545595782313	-0.5970234444284345
		>50K		<=50K

Error sum for iteration 82600 = 56.50983542364114

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7538692149477502	-0.6976823663223062	age
Hidden Weights:
	-0.8329983056913001	1.015531224099363
	0.3319516326946654	-0.5970205175403573
		>50K		<=50K

Error sum for iteration 82700 = 56.50983541575955

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.753935519652363	-0.697731415763613	age
Hidden Weights:
	-0.8329973053169162	1.0155302236776715
	0.3319487084111799	-0.597017593252381
		>50K		<=50K

Error sum for iteration 82800 = 56.50983540789582

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7540017448001767	-0.6977804210853465	age
Hidden Weights:
	-0.8329963061352581	1.015529224448807
	0.33194578672312886	-0.5970146715598269
		>50K		<=50K

Error sum for iteration 82900 = 56.509835400049866

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7540678905823889	-0.6978293823671359	age
Hidden Weights:
	-0.8329953081434683	1.0155282264098873
	0.33194286762586095	-0.5970117524580729
		>50K		<=50K

Error sum for iteration 83000 = 56.50983539222147

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7541339571896372	-0.6978782996882513	age
Hidden Weights:
	-0.8329943113386907	1.0155272295580928
	0.33193995111473146	-0.5970088359424888
		>50K		<=50K

Error sum for iteration 83100 = 56.50983538441095

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7541999448117936	-0.6979271731278541	age
Hidden Weights:
	-0.8329933157180898	1.015526233890559
	0.3319370371851292	-0.5970059220084154
		>50K		<=50K

Error sum for iteration 83200 = 56.50983537661777

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7542658536380737	-0.6979760027648471	age
Hidden Weights:
	-0.8329923212788537	1.0155252394044922
	0.33193412583242454	-0.5970030106512297
		>50K		<=50K

Error sum for iteration 83300 = 56.50983536884216

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7543316838570648	-0.6980247886780429	age
Hidden Weights:
	-0.8329913280181516	1.0155242460970533
	0.3319312170520278	-0.597000101866391
		>50K		<=50K

Error sum for iteration 83400 = 56.509835361084086

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7543974356565609	-0.6980735309458512	age
Hidden Weights:
	-0.8329903359331765	1.0155232539654462
	0.3319283108393536	-0.596997195649296
		>50K		<=50K

Error sum for iteration 83500 = 56.50983535334327

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7544631092237944	-0.6981222296465895	age
Hidden Weights:
	-0.832989345021143	1.0155222630068697
	0.33192540718981267	-0.5969942919953594
		>50K		<=50K

Error sum for iteration 83600 = 56.509835345619926

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7545287047452646	-0.6981708848583812	age
Hidden Weights:
	-0.8329883552792541	1.0155212732185193
	0.33192250609887775	-0.5969913909000316
		>50K		<=50K

Error sum for iteration 83700 = 56.509835337913806

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7545942224068823	-0.6982194966590809	age
Hidden Weights:
	-0.8329873667047333	1.015520284597639
	0.33191960756198835	-0.5969884923587668
		>50K		<=50K

Error sum for iteration 83800 = 56.50983533022496

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.754659662393771	-0.6982680651263043	age
Hidden Weights:
	-0.8329863792948113	1.015519297141454
	0.3319167115746114	-0.596985596366984
		>50K		<=50K

Error sum for iteration 83900 = 56.50983532255311

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7547250248905054	-0.6983165903375396	age
Hidden Weights:
	-0.8329853930467457	1.0155183108472177
	0.331913818132223	-0.5969827029201578
		>50K		<=50K

Error sum for iteration 84000 = 56.509835314898424

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7547903100809128	-0.6983650723700476	age
Hidden Weights:
	-0.8329844079577735	1.015517325712185
	0.33191092723028515	-0.5969798120137799
		>50K		<=50K

Error sum for iteration 84100 = 56.50983530726096

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7548555181481741	-0.6984135113008423	age
Hidden Weights:
	-0.8329834240251655	1.0155163417335669
	0.3319080388643077	-0.5969769236433535
		>50K		<=50K

Error sum for iteration 84200 = 56.50983529964031

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.754920649274883	-0.6984619072067855	age
Hidden Weights:
	-0.8329824412461978	1.0155153589086972
	0.331905153029827	-0.5969740378043679
		>50K		<=50K

Error sum for iteration 84300 = 56.509835292036456

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7549857036429987	-0.6985102601644377	age
Hidden Weights:
	-0.8329814596181377	1.015514377234824
	0.33190226972232884	-0.5969711544923991
		>50K		<=50K

Error sum for iteration 84400 = 56.5098352844497

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.755050681433784	-0.6985585702503261	age
Hidden Weights:
	-0.8329804791382919	1.0155133967092644
	0.33189938893735477	-0.5969682737029912
		>50K		<=50K

Error sum for iteration 84500 = 56.50983527687969

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7551155828278192	-0.6986068375406207	age
Hidden Weights:
	-0.8329794998039545	1.0155124173292889
	0.3318965106704648	-0.5969653954316718
		>50K		<=50K

Error sum for iteration 84600 = 56.50983526932638

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7551804080051546	-0.6986550621112793	age
Hidden Weights:
	-0.8329785216124431	1.015511439092228
	0.33189363491720664	-0.5969625196739957
		>50K		<=50K

Error sum for iteration 84700 = 56.50983526178984

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7552451571451119	-0.6987032440381233	age
Hidden Weights:
	-0.8329775445610514	1.0155104619954032
	0.331890761673141	-0.596959646425564
		>50K		<=50K

Error sum for iteration 84800 = 56.50983525426989

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7553098304263818	-0.698751383396813	age
Hidden Weights:
	-0.832976568647142	1.0155094860361384
	0.3318878909338648	-0.5969567756819318
		>50K		<=50K

Error sum for iteration 84900 = 56.50983524676662

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7553744280270566	-0.6987994802626893	age
Hidden Weights:
	-0.8329755938680362	1.0155085112117612
	0.3318850226949639	-0.5969539074386796
		>50K		<=50K

Error sum for iteration 85000 = 56.5098352392798

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7554389501246295	-0.6988475347109954	age
Hidden Weights:
	-0.8329746202210903	1.015507537519636
	0.3318821569520225	-0.5969510416914646
		>50K		<=50K

Error sum for iteration 85100 = 56.50983523180947

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7555033968959468	-0.6988955468167342	age
Hidden Weights:
	-0.8329736477036587	1.0155065649570982
	0.3318792937006714	-0.5969481784358813
		>50K		<=50K

Error sum for iteration 85200 = 56.509835224355584

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7555677685171671	-0.6989435166547695	age
Hidden Weights:
	-0.8329726763130999	1.015505593521544
	0.3318764329365517	-0.5969453176674923
		>50K		<=50K

Error sum for iteration 85300 = 56.50983521691799

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.755632065163898	-0.6989914442996609	age
Hidden Weights:
	-0.8329717060468013	1.0155046232103346
	0.33187357465529876	-0.596942459381962
		>50K		<=50K

Error sum for iteration 85400 = 56.50983520949688

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7556962870111519	-0.6990393298258373	age
Hidden Weights:
	-0.8329707369021404	1.0155036540208504
	0.33187071885259795	-0.5969396035749625
		>50K		<=50K

Error sum for iteration 85500 = 56.50983520209187

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7557604342332966	-0.6990871733074563	age
Hidden Weights:
	-0.8329697688765132	1.015502685950493
	0.33186786552407727	-0.5969367502421238
		>50K		<=50K

Error sum for iteration 85600 = 56.509835194703065

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7558245070041292	-0.6991349748186115	age
Hidden Weights:
	-0.8329688019673327	1.0155017189966604
	0.3318650146653983	-0.59693389937921
		>50K		<=50K

Error sum for iteration 85700 = 56.50983518733053

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.75588850549669	-0.6991827344331379	age
Hidden Weights:
	-0.8329678361720034	1.0155007531567546
	0.33186216627226006	-0.5969310509818696
		>50K		<=50K

Error sum for iteration 85800 = 56.50983517997396

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.755952429883647	-0.6992304522246129	age
Hidden Weights:
	-0.8329668714879426	1.0154997884282237
	0.3318593203403832	-0.5969282050457396
		>50K		<=50K

Error sum for iteration 85900 = 56.50983517263342

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7560162803369019	-0.699278128266512	age
Hidden Weights:
	-0.8329659079125838	1.0154988248084784
	0.33185647686543845	-0.5969253615665637
		>50K		<=50K

Error sum for iteration 86000 = 56.50983516530903

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7560800570277805	-0.6993257626320631	age
Hidden Weights:
	-0.8329649454433689	1.0154978622949704
	0.3318536358431577	-0.5969225205400639
		>50K		<=50K

Error sum for iteration 86100 = 56.50983515800052

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7561437601271035	-0.6993733553942859	age
Hidden Weights:
	-0.8329639840777509	1.0154969008851413
	0.33185079726929334	-0.5969196819619849
		>50K		<=50K

Error sum for iteration 86200 = 56.509835150707744

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7562073898050283	-0.6994209066260484	age
Hidden Weights:
	-0.8329630238131694	1.015495940576447
	0.33184796113958187	-0.5969168458280489
		>50K		<=50K

Error sum for iteration 86300 = 56.509835143430976

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7562709462310049	-0.6994684164000107	age
Hidden Weights:
	-0.8329620646471073	1.015494981366348
	0.3318451274497195	-0.5969140121340087
		>50K		<=50K

Error sum for iteration 86400 = 56.50983513616998

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7563344295741127	-0.699515884788718	age
Hidden Weights:
	-0.8329611065770248	1.0154940232523175
	0.33184229619553607	-0.5969111808756783
		>50K		<=50K

Error sum for iteration 86500 = 56.509835128924585

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7563978400027334	-0.6995633118644359	age
Hidden Weights:
	-0.832960149600413	1.0154930662318484
	0.33183946737279785	-0.5969083520487244
		>50K		<=50K

Error sum for iteration 86600 = 56.50983512169486

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7564611776847159	-0.6996106976992166	age
Hidden Weights:
	-0.8329591937147712	1.0154921103024177
	0.33183664097726495	-0.5969055256489925
		>50K		<=50K

Error sum for iteration 86700 = 56.50983511448091

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7565244427872578	-0.6996580423649384	age
Hidden Weights:
	-0.8329582389175948	1.015491155461542
	0.33183381700475817	-0.596902701672252
		>50K		<=50K

Error sum for iteration 86800 = 56.50983510728256

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7565876354770684	-0.6997053459333458	age
Hidden Weights:
	-0.8329572852063885	1.0154902017067233
	0.331830995451076	-0.5968998801143787
		>50K		<=50K

Error sum for iteration 86900 = 56.509835100099515

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7566507559202098	-0.6997526084759664	age
Hidden Weights:
	-0.8329563325786672	1.0154892490354712
	0.3318281763120295	-0.5968970609711157
		>50K		<=50K

Error sum for iteration 87000 = 56.50983509293202

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7567138042821343	-0.6997998300641413	age
Hidden Weights:
	-0.8329553810319642	1.0154882974453312
	0.3318253595834729	-0.5968942442383516
		>50K		<=50K

Error sum for iteration 87100 = 56.50983508577999

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7567767807278911	-0.6998470107690334	age
Hidden Weights:
	-0.8329544305638157	1.0154873469338284
	0.33182254526124777	-0.5968914299119177
		>50K		<=50K

Error sum for iteration 87200 = 56.50983507864345

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7568396854217668	-0.699894150661604	age
Hidden Weights:
	-0.8329534811717546	1.0154863974985069
	0.33181973334119297	-0.5968886179876506
		>50K		<=50K

Error sum for iteration 87300 = 56.50983507152201

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.756902518527644	-0.6999412498126462	age
Hidden Weights:
	-0.8329525328533525	1.015485449136906
	0.3318169238191685	-0.5968858084614034
		>50K		<=50K

Error sum for iteration 87400 = 56.509835064415924

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.756965280208726	-0.6999883082927603	age
Hidden Weights:
	-0.8329515856061556	1.0154845018466065
	0.3318141166910321	-0.5968830013290511
		>50K		<=50K

Error sum for iteration 87500 = 56.50983505732509

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7570279706277133	-0.7000353261723723	age
Hidden Weights:
	-0.8329506394277354	1.0154835556251658
	0.33181131195267555	-0.596880196586523
		>50K		<=50K

Error sum for iteration 87600 = 56.509835050249386

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.75709058994681	-0.7000823035217549	age
Hidden Weights:
	-0.832949694315668	1.0154826104701489
	0.33180850960001074	-0.596877394229695
		>50K		<=50K

Error sum for iteration 87700 = 56.50983504318884

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7571531383275543	-0.7001292404109386	age
Hidden Weights:
	-0.8329487502675286	1.015481666379156
	0.33180570962891365	-0.5968745942545362
		>50K		<=50K

Error sum for iteration 87800 = 56.50983503614343

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7572156159310459	-0.7001761369097936	age
Hidden Weights:
	-0.832947807280926	1.0154807233497736
	0.3318029120353049	-0.5968717966568227
		>50K		<=50K

Error sum for iteration 87900 = 56.509835029112935

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7572780229177197	-0.7002229930879857	age
Hidden Weights:
	-0.8329468653534489	1.0154797813796002
	0.3318001168151045	-0.596869001432531
		>50K		<=50K

Error sum for iteration 88000 = 56.509835022097405

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7573403594475444	-0.7002698090150463	age
Hidden Weights:
	-0.8329459244827155	1.0154788404662556
	0.3317973239642692	-0.5968662085776325
		>50K		<=50K

Error sum for iteration 88100 = 56.509835015096805

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7574026256799041	-0.7003165847603174	age
Hidden Weights:
	-0.8329449846663398	1.0154779006073524
	0.33179453347874377	-0.5968634180880743
		>50K		<=50K

Error sum for iteration 88200 = 56.50983500811119

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7574648217736469	-0.7003633203929737	age
Hidden Weights:
	-0.8329440459019424	1.0154769618005117
	0.3317917453544952	-0.5968606299597693
		>50K		<=50K

Error sum for iteration 88300 = 56.50983500114031

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.75752694788712	-0.7004100159819404	age
Hidden Weights:
	-0.8329431081871599	1.0154760240433718
	0.3317889595875105	-0.5968578441886495
		>50K		<=50K

Error sum for iteration 88400 = 56.509834994184224

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7575890041780985	-0.7004566715960453	age
Hidden Weights:
	-0.8329421715196471	1.015475087333566
	0.3317861761737511	-0.5968550607707903
		>50K		<=50K

Error sum for iteration 88500 = 56.50983498724285

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7576509908037872	-0.700503287303867	age
Hidden Weights:
	-0.8329412358970354	1.0154741516687538
	0.3317833951091912	-0.5968522797021608
		>50K		<=50K

Error sum for iteration 88600 = 56.509834980316214

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7577129079209389	-0.7005498631738576	age
Hidden Weights:
	-0.8329403013169928	1.015473217046573
	0.3317806163898455	-0.5968495009787362
		>50K		<=50K

Error sum for iteration 88700 = 56.509834973404196

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7577747556857793	-0.7005963992742896	age
Hidden Weights:
	-0.8329393677771847	1.0154722834647147
	0.3317778400117212	-0.5968467245964986
		>50K		<=50K

Error sum for iteration 88800 = 56.509834966506745

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7578365342539158	-0.7006428956732766	age
Hidden Weights:
	-0.8329384352752724	1.0154713509208297
	0.33177506597082834	-0.5968439505515526
		>50K		<=50K

Error sum for iteration 88900 = 56.50983495962389

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7578982437805366	-0.7006893524387184	age
Hidden Weights:
	-0.8329375038089463	1.015470419412622
	0.3317722942632036	-0.596841178839872
		>50K		<=50K

Error sum for iteration 89000 = 56.509834952755504

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7579598844202678	-0.7007357696383553	age
Hidden Weights:
	-0.8329365733758913	1.0154694889377647
	0.3317695248848853	-0.5968384094574479
		>50K		<=50K

Error sum for iteration 89100 = 56.509834945901616

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7580214563271601	-0.7007821473397231	age
Hidden Weights:
	-0.8329356439738078	1.0154685594939599
	0.33176675783189863	-0.596835642400405
		>50K		<=50K

Error sum for iteration 89200 = 56.50983493906207

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.758082959654804	-0.7008284856102281	age
Hidden Weights:
	-0.8329347156004103	1.0154676310789146
	0.33176399310030635	-0.5968328776648237
		>50K		<=50K

Error sum for iteration 89300 = 56.509834932236856

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.758144394556267	-0.7008747845171129	age
Hidden Weights:
	-0.8329337882533937	1.0154667036903229
	0.3317612306861935	-0.5968301152467131
		>50K		<=50K

Error sum for iteration 89400 = 56.509834925426134

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7582057611840939	-0.7009210441274589	age
Hidden Weights:
	-0.8329328619304815	1.0154657773259157
	0.3317584705856504	-0.5968273551421729
		>50K		<=50K

Error sum for iteration 89500 = 56.50983491862956

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7582670596903561	-0.7009672645081044	age
Hidden Weights:
	-0.8329319366294032	1.0154648519834273
	0.3317557127947194	-0.5968245973473141
		>50K		<=50K

Error sum for iteration 89600 = 56.509834911847115

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7583282902265472	-0.7010134457257442	age
Hidden Weights:
	-0.8329310123478996	1.0154639276605797
	0.3317529573095393	-0.5968218418582089
		>50K		<=50K

Error sum for iteration 89700 = 56.50983490507898

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7583894529437517	-0.7010595878468774	age
Hidden Weights:
	-0.8329300890836989	1.015463004355124
	0.33175020412624745	-0.5968190886709438
		>50K		<=50K

Error sum for iteration 89800 = 56.50983489832502

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7584505479924539	-0.7011056909379064	age
Hidden Weights:
	-0.8329291668345581	1.0154620820648053
	0.3317474532409125	-0.5968163377816659
		>50K		<=50K

Error sum for iteration 89900 = 56.50983489158497

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7585115755226653	-0.7011517550650436	age
Hidden Weights:
	-0.8329282455982394	1.0154611607873787
	0.33174470464968164	-0.5968135891864788
		>50K		<=50K

Error sum for iteration 90000 = 56.509834884859

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7585725356839441	-0.7011977802943173	age
Hidden Weights:
	-0.8329273253725017	1.0154602405206183
	0.3317419583487231	-0.596810842881562
		>50K		<=50K

Error sum for iteration 90100 = 56.509834878147224

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7586334286253129	-0.7012437666916408	age
Hidden Weights:
	-0.832926406155122	1.0154593212622773
	0.33173921433416775	-0.5968080988630844
		>50K		<=50K

Error sum for iteration 90200 = 56.509834871449335

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.758694254495296	-0.7012897143226388	age
Hidden Weights:
	-0.8329254879438717	1.0154584030101497
	0.33173647260216405	-0.5968053571271525
		>50K		<=50K

Error sum for iteration 90300 = 56.5098348647652

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7587550134419795	-0.701335623252811	age
Hidden Weights:
	-0.8329245707365422	1.0154574857620355
	0.33173373314885696	-0.5968026176699248
		>50K		<=50K

Error sum for iteration 90400 = 56.50983485809518

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7588157056128488	-0.7013814935475535	age
Hidden Weights:
	-0.8329236545309284	1.0154565695157023
	0.3317309959704641	-0.5967998804875951
		>50K		<=50K

Error sum for iteration 90500 = 56.50983485143877

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7588763311550274	-0.7014273252720812	age
Hidden Weights:
	-0.8329227393248303	1.0154556542689703
	0.3317282610631479	-0.5967971455763562
		>50K		<=50K

Error sum for iteration 90600 = 56.509834844796124

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7589368902150777	-0.7014731184914119	age
Hidden Weights:
	-0.8329218251160561	1.0154547400196374
	0.33172552842312353	-0.5967944129324396
		>50K		<=50K

Error sum for iteration 90700 = 56.509834838167386

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7589973829391355	-0.7015188732703994	age
Hidden Weights:
	-0.8329209119024213	1.015453826765516
	0.3317227980465763	-0.5967916825520293
		>50K		<=50K

Error sum for iteration 90800 = 56.50983483155225

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7590578094728158	-0.7015645896737656	age
Hidden Weights:
	-0.8329199996817568	1.0154529145044418
	0.33172006992974057	-0.5967889544313092
		>50K		<=50K

Error sum for iteration 90900 = 56.50983482495073

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7591181699611727	-0.7016102677660456	age
Hidden Weights:
	-0.8329190884518789	1.01545200323423
	0.3317173440688476	-0.5967862285665749
		>50K		<=50K

Error sum for iteration 91000 = 56.509834818362904

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7591784645488929	-0.7016559076115632	age
Hidden Weights:
	-0.8329181782106395	1.0154510929527194
	0.33171462046012373	-0.5967835049539699
		>50K		<=50K

Error sum for iteration 91100 = 56.50983481178872

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7592386933802081	-0.7017015092745927	age
Hidden Weights:
	-0.8329172689558666	1.015450183657758
	0.33171189909980625	-0.5967807835897849
		>50K		<=50K

Error sum for iteration 91200 = 56.50983480522795

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7592988565987906	-0.7017470728191861	age
Hidden Weights:
	-0.8329163606854281	1.0154492753472002
	0.33170917998414823	-0.5967780644702778
		>50K		<=50K

Error sum for iteration 91300 = 56.509834798680636

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7593589543478614	-0.7017925983092747	age
Hidden Weights:
	-0.8329154533971806	1.0154483680189021
	0.3317064631094288	-0.5967753475916973
		>50K		<=50K

Error sum for iteration 91400 = 56.50983479214674

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.759418986770236	-0.7018380858085206	age
Hidden Weights:
	-0.8329145470889789	1.0154474616707367
	0.3317037484719253	-0.596772632950362
		>50K		<=50K

Error sum for iteration 91500 = 56.50983478562618

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7594789540082237	-0.7018835353805124	age
Hidden Weights:
	-0.8329136417587012	1.0154465563005761
	0.331701036067912	-0.5967699205425188
		>50K		<=50K

Error sum for iteration 91600 = 56.50983477911926

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7595388562035722	-0.7019289470886174	age
Hidden Weights:
	-0.8329127374042199	1.0154456519062791
	0.33169832589369574	-0.596767210364452
		>50K		<=50K

Error sum for iteration 91700 = 56.50983477262537

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7595986934976959	-0.7019743209961264	age
Hidden Weights:
	-0.832911834023433	1.0154447484857496
	0.3316956179455568	-0.5967645024124544
		>50K		<=50K

Error sum for iteration 91800 = 56.509834766144884

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7596584660315219	-0.7020196571661238	age
Hidden Weights:
	-0.8329109316142338	1.015443846036881
	0.3316929122197997	-0.5967617966828294
		>50K		<=50K

Error sum for iteration 91900 = 56.509834759677645

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.759718173945513	-0.7020649556615343	age
Hidden Weights:
	-0.8329100301745157	1.0154429445575703
	0.33169020871274596	-0.5967590931718937
		>50K		<=50K

Error sum for iteration 92000 = 56.50983475322353

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7597778173796406	-0.7021102165451184	age
Hidden Weights:
	-0.8329091297021894	1.0154420440457304
	0.33168750742074576	-0.5967563918759979
		>50K		<=50K

Error sum for iteration 92100 = 56.50983474678259

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7598373964734285	-0.7021554398794663	age
Hidden Weights:
	-0.8329082301951659	1.0154411444992397
	0.33168480834010616	-0.5967536927915248
		>50K		<=50K

Error sum for iteration 92200 = 56.509834740354776

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7598969113659642	-0.7022006257271318	age
Hidden Weights:
	-0.8329073316513629	1.015440245916053
	0.33168211146718507	-0.5967509959147804
		>50K		<=50K

Error sum for iteration 92300 = 56.509834733940004

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7599563621959194	-0.702245774150371	age
Hidden Weights:
	-0.8329064340687147	1.0154393482940933
	0.33167941679832247	-0.5967483012421547
		>50K		<=50K

Error sum for iteration 92400 = 56.50983472753831

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7600157491014594	-0.7022908852113235	age
Hidden Weights:
	-0.8329055374451461	1.0154384516312778
	0.3316767243299135	-0.596745608769964
		>50K		<=50K

Error sum for iteration 92500 = 56.509834721149446

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7600750722203545	-0.7023359589720263	age
Hidden Weights:
	-0.832904641778607	1.015437555925575
	0.3316740340583326	-0.596742918494559
		>50K		<=50K

Error sum for iteration 92600 = 56.50983471477374

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7601343316899339	-0.7023809954942833	age
Hidden Weights:
	-0.8329037470670418	1.015436661174918
	0.3316713459799669	-0.5967402304123839
		>50K		<=50K

Error sum for iteration 92700 = 56.509834708410786

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7601935276470058	-0.7024259948397716	age
Hidden Weights:
	-0.8329028533083964	1.015435767377257
	0.33166866009118673	-0.596737544519755
		>50K		<=50K

Error sum for iteration 92800 = 56.50983470206089

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7602526602279789	-0.7024709570700817	age
Hidden Weights:
	-0.8329019605006378	1.0154348745305497
	0.33166597638843054	-0.5967348608131426
		>50K		<=50K

Error sum for iteration 92900 = 56.50983469572368

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7603117295687999	-0.7025158822465977	age
Hidden Weights:
	-0.8329010686417361	1.015433982632769
	0.331663294868066	-0.5967321792890132
		>50K		<=50K

Error sum for iteration 93000 = 56.50983468939928

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7603707358050188	-0.7025607704305196	age
Hidden Weights:
	-0.8329001777296651	1.0154330916818866
	0.3316606155265155	-0.5967294999437046
		>50K		<=50K

Error sum for iteration 93100 = 56.509834683087625

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7604296790716835	-0.7026056216829122	age
Hidden Weights:
	-0.8328992877623946	1.0154322016758786
	0.3316579383602147	-0.5967268227736515
		>50K		<=50K

Error sum for iteration 93200 = 56.50983467678868

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7604885595035977	-0.7026504360647101	age
Hidden Weights:
	-0.832898398737922	1.0154313126127255
	0.3316552633656183	-0.5967241477752858
		>50K		<=50K

Error sum for iteration 93300 = 56.50983467050242

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.760547377234892	-0.7026952136367038	age
Hidden Weights:
	-0.8328975106542293	1.015430424490443
	0.3316525905391691	-0.596721474945024
		>50K		<=50K

Error sum for iteration 93400 = 56.50983466422868

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7606061323993889	-0.7027399544594726	age
Hidden Weights:
	-0.8328966235093289	1.015429537307023
	0.3316499198772977	-0.5967188042793297
		>50K		<=50K

Error sum for iteration 93500 = 56.509834657967765

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.760664825130474	-0.7027846585935296	age
Hidden Weights:
	-0.8328957373012111	1.0154286510604542
	0.33164725137648726	-0.5967161357746776
		>50K		<=50K

Error sum for iteration 93600 = 56.50983465171929

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7607234555611049	-0.70282932609921	age
Hidden Weights:
	-0.832894852027904	1.0154277657487625
	0.33164458503320904	-0.5967134694275542
		>50K		<=50K

Error sum for iteration 93700 = 56.50983464548338

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7607820238237463	-0.7028739570367061	age
Hidden Weights:
	-0.8328939676874152	1.0154268813699572
	0.33164192084391464	-0.5967108052344535
		>50K		<=50K

Error sum for iteration 93800 = 56.50983463925985

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7608405300505394	-0.7029185514660306	age
Hidden Weights:
	-0.8328930842777759	1.0154259979220714
	0.33163925880509243	-0.5967081431918896
		>50K		<=50K

Error sum for iteration 93900 = 56.50983463304883

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7608989743731887	-0.702963109447064	age
Hidden Weights:
	-0.8328922017970072	1.015425115403121
	0.33163659891325953	-0.5967054832962858
		>50K		<=50K

Error sum for iteration 94000 = 56.50983462685019

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7609573569228836	-0.7030076310395533	age
Hidden Weights:
	-0.8328913202431563	1.015424233811161
	0.3316339411649289	-0.5967028255441261
		>50K		<=50K

Error sum for iteration 94100 = 56.5098346206639

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7610156778305237	-0.7030521163030141	age
Hidden Weights:
	-0.8328904396142585	1.0154233531442265
	0.3316312855566039	-0.5967001699319946
		>50K		<=50K

Error sum for iteration 94200 = 56.509834614489996

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7610739372265455	-0.7030965652969542	age
Hidden Weights:
	-0.8328895599083688	1.0154224734003705
	0.3316286320847835	-0.596697516456443
		>50K		<=50K

Error sum for iteration 94300 = 56.5098346083284

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7611321352409299	-0.703140978080685	age
Hidden Weights:
	-0.8328886811235438	1.0154215945776466
	0.33162598074602473	-0.5966948651139482
		>50K		<=50K

Error sum for iteration 94400 = 56.50983460217898

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7611902720033016	-0.7031853547133192	age
Hidden Weights:
	-0.8328878032578422	1.0154207166741058
	0.33162333153685625	-0.5966922159010433
		>50K		<=50K

Error sum for iteration 94500 = 56.509834596041934

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7612483476428363	-0.7032296952538901	age
Hidden Weights:
	-0.8328869263093371	1.0154198396878187
	0.33162068445383447	-0.5966895688143282
		>50K		<=50K

Error sum for iteration 94600 = 56.50983458991694

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.761306362288319	-0.7032739997611939	age
Hidden Weights:
	-0.8328860502760935	1.0154189636168724
	0.3316180394934986	-0.5966869238503445
		>50K		<=50K

Error sum for iteration 94700 = 56.50983458380414

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7613643160681041	-0.70331826829398	age
Hidden Weights:
	-0.8328851751562036	1.0154180884593498
	0.3316153966524388	-0.5966842810056144
		>50K		<=50K

Error sum for iteration 94800 = 56.50983457770333

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7614222091101277	-0.7033625009107694	age
Hidden Weights:
	-0.832884300947747	1.0154172142133298
	0.3316127559272204	-0.5966816402767405
		>50K		<=50K

Error sum for iteration 94900 = 56.509834571614654

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7614800415420243	-0.7034066976700856	age
Hidden Weights:
	-0.8328834276488062	1.0154163408769028
	0.33161011731440965	-0.5966790016603192
		>50K		<=50K

Error sum for iteration 95000 = 56.50983456553803

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.761537813490888	-0.703450858630173	age
Hidden Weights:
	-0.8328825552574946	1.015415468448159
	0.3316074808106216	-0.5966763651528967
		>50K		<=50K

Error sum for iteration 95100 = 56.50983455947349

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7615955250835836	-0.7034949838491453	age
Hidden Weights:
	-0.8328816837719095	1.0154145969252086
	0.33160484641242394	-0.5966737307510828
		>50K		<=50K

Error sum for iteration 95200 = 56.50983455342077

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7616531764464176	-0.7035390733850717	age
Hidden Weights:
	-0.8328808131901623	1.0154137263061696
	0.3316022141164504	-0.59667109845144
		>50K		<=50K

Error sum for iteration 95300 = 56.50983454738017

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.761710767705372	-0.7035831272957886	age
Hidden Weights:
	-0.8328799435103696	1.0154128565891514
	0.33159958391929095	-0.5966684682506663
		>50K		<=50K

Error sum for iteration 95400 = 56.509834541351296

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7617682989859808	-0.7036271456389649	age
Hidden Weights:
	-0.8328790747306555	1.015411987772265
	0.3315969558175839	-0.5966658401453734
		>50K		<=50K

Error sum for iteration 95500 = 56.50983453533434

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.761825770413427	-0.7036711284722612	age
Hidden Weights:
	-0.8328782068491415	1.0154111198536586
	0.3315943298079703	-0.5966632141321644
		>50K		<=50K

Error sum for iteration 95600 = 56.50983452932917

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7618831821125412	-0.7037150758530363	age
Hidden Weights:
	-0.8328773398639727	1.0154102528314555
	0.3315917058870756	-0.5966605902076496
		>50K		<=50K

Error sum for iteration 95700 = 56.50983452333585

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.761940534207694	-0.7037589878386541	age
Hidden Weights:
	-0.8328764737732848	1.015409386703801
	0.3315890840515379	-0.5966579683685308
		>50K		<=50K

Error sum for iteration 95800 = 56.50983451735424

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7619978268229114	-0.7038028644862563	age
Hidden Weights:
	-0.8328756085752137	1.0154085214688375
	0.3315864642980466	-0.59665534861142
		>50K		<=50K

Error sum for iteration 95900 = 56.509834511384426

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7620550600817858	-0.7038467058529215	age
Hidden Weights:
	-0.8328747442679129	1.0154076571247013
	0.331583846623254	-0.5966527309330225
		>50K		<=50K

Error sum for iteration 96000 = 56.50983450542626

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7621122341075742	-0.7038905119954624	age
Hidden Weights:
	-0.832873880849543	1.0154067936695694
	0.33158123102381826	-0.5966501153299831
		>50K		<=50K

Error sum for iteration 96100 = 56.50983449947948

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7621693490231237	-0.7039342829706582	age
Hidden Weights:
	-0.8328730183182705	1.015405931101597
	0.3315786174964164	-0.5966475017990714
		>50K		<=50K

Error sum for iteration 96200 = 56.509834493544595

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7622264049508833	-0.7039780188350656	age
Hidden Weights:
	-0.8328721566722619	1.0154050694189514
	0.33157600603774934	-0.5966448903368644
		>50K		<=50K

Error sum for iteration 96300 = 56.50983448762128

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7622834020129721	-0.7040217196452022	age
Hidden Weights:
	-0.8328712959096874	1.015404208619799
	0.3315733966445263	-0.5966422809400638
		>50K		<=50K

Error sum for iteration 96400 = 56.50983448170937

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7623403403310963	-0.7040653854574019	age
Hidden Weights:
	-0.8328704360287236	1.015403348702346
	0.3315707893134283	-0.5966396736053691
		>50K		<=50K

Error sum for iteration 96500 = 56.509834475809264

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7623972200265839	-0.7041090163279077	age
Hidden Weights:
	-0.8328695770275678	1.0154024896647533
	0.33156818404116084	-0.5966370683295624
		>50K		<=50K

Error sum for iteration 96600 = 56.50983446992038

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7624540412204164	-0.7041526123127049	age
Hidden Weights:
	-0.8328687189044061	1.015401631505202
	0.3315655808244554	-0.5966344651092943
		>50K		<=50K

Error sum for iteration 96700 = 56.50983446404302

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7625108040330775	-0.7041961734677551	age
Hidden Weights:
	-0.8328678616574294	1.0154007742219162
	0.3315629796600413	-0.5966318639413205
		>50K		<=50K

Error sum for iteration 96800 = 56.50983445817693

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7625675085849002	-0.7042396998488972	age
Hidden Weights:
	-0.8328670052848444	1.0153999178130941
	0.3315603805446343	-0.5966292648223797
		>50K		<=50K

Error sum for iteration 96900 = 56.509834452322316

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7626241549955929	-0.7042831915117611	age
Hidden Weights:
	-0.8328661497848585	1.015399062276926
	0.33155778347495424	-0.5966266677492598
		>50K		<=50K

Error sum for iteration 97000 = 56.50983444647905

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7626807433846876	-0.7043266485118496	age
Hidden Weights:
	-0.8328652951556751	1.0153982076116241
	0.331555188447831	-0.5966240727186287
		>50K		<=50K

Error sum for iteration 97100 = 56.50983444064711

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7627372738712851	-0.7043700709045587	age
Hidden Weights:
	-0.8328644413955323	1.0153973538154257
	0.3315525954599761	-0.5966214797272044
		>50K		<=50K

Error sum for iteration 97200 = 56.509834434826345

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7627937465741326	-0.7044134587451614	age
Hidden Weights:
	-0.8328635885026388	1.015396500886552
	0.3315500045081713	-0.5966188887718138
		>50K		<=50K

Error sum for iteration 97300 = 56.50983442901693

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7628501616116036	-0.7044568120888202	age
Hidden Weights:
	-0.8328627364752287	1.0153956488232099
	0.331547415589169	-0.596616299849277
		>50K		<=50K

Error sum for iteration 97400 = 56.50983442321868

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.76290651910171	-0.7045001309904769	age
Hidden Weights:
	-0.8328618853115358	1.015394797623649
	0.3315448286997876	-0.5966137129563728
		>50K		<=50K

Error sum for iteration 97500 = 56.50983441743164

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7629628191620229	-0.7045434155050102	age
Hidden Weights:
	-0.832861035009803	1.0153939472861109
	0.33154224383679565	-0.5966111280898075
		>50K		<=50K

Error sum for iteration 97600 = 56.509834411655824

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7630190619098667	-0.7045866656871854	age
Hidden Weights:
	-0.8328601855682788	1.0153930978088466
	0.33153966099697657	-0.5966085452463893
		>50K		<=50K

Error sum for iteration 97700 = 56.5098344058909

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7630752474621851	-0.7046298815915445	age
Hidden Weights:
	-0.8328593369852112	1.0153922491900922
	0.33153708017710304	-0.5966059644230227
		>50K		<=50K

Error sum for iteration 97800 = 56.5098344001372

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7631313759355317	-0.7046730632725683	age
Hidden Weights:
	-0.8328584892588582	1.0153914014281151
	0.3315345013740429	-0.5966033856164678
		>50K		<=50K

Error sum for iteration 97900 = 56.509834394394495

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7631874474461019	-0.7047162107846789	age
Hidden Weights:
	-0.8328576423874676	1.0153905545211728
	0.3315319245846124	-0.5966008088234683
		>50K		<=50K

Error sum for iteration 98000 = 56.50983438866286

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7632434621097549	-0.704759324182068	age
Hidden Weights:
	-0.8328567963693252	1.0153897084675356
	0.33152934980558957	-0.5965982340409371
		>50K		<=50K

Error sum for iteration 98100 = 56.509834382942174

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7632994200419626	-0.7048024035188504	age
Hidden Weights:
	-0.8328559512026953	1.0153888632654662
	0.33152677703383043	-0.5965956612656546
		>50K		<=50K

Error sum for iteration 98200 = 56.509834377232465

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7633553213579305	-0.7048454488488946	age
Hidden Weights:
	-0.8328551068858551	1.015388018913253
	0.33152420626618645	-0.5965930904945226
		>50K		<=50K

Error sum for iteration 98300 = 56.50983437153371

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7634111661724141	-0.7048884602261037	age
Hidden Weights:
	-0.8328542634170841	1.0153871754091723
	0.3315216374995244	-0.5965905217243743
		>50K		<=50K

Error sum for iteration 98400 = 56.50983436584566

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7634669545998796	-0.7049314377041412	age
Hidden Weights:
	-0.8328534207946825	1.015386332751512
	0.33151907073066567	-0.5965879549520413
		>50K		<=50K

Error sum for iteration 98500 = 56.50983436016867

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7635226867543494	-0.7049743813366353	age
Hidden Weights:
	-0.8328525790169283	1.0153854909385733
	0.3315165059564908	-0.5965853901743868
		>50K		<=50K

Error sum for iteration 98600 = 56.50983435450233

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7635783627496743	-0.7050172911769308	age
Hidden Weights:
	-0.8328517380821351	1.0153846499686479
	0.3315139431739013	-0.596582827388284
		>50K		<=50K

Error sum for iteration 98700 = 56.50983434884695

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7636339826992322	-0.7050601672783983	age
Hidden Weights:
	-0.832850897988596	1.0153838098400327
	0.33151138237976085	-0.5965802665906361
		>50K		<=50K

Error sum for iteration 98800 = 56.50983434320221

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.763689546716106	-0.7051030096942519	age
Hidden Weights:
	-0.8328500587346163	1.0153829705510602
	0.33150882357092964	-0.5965777077783613
		>50K		<=50K

Error sum for iteration 98900 = 56.509834337568236

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7637450549129884	-0.7051458184775707	age
Hidden Weights:
	-0.8328492203185248	1.015382132100017
	0.331506266744337	-0.596575150948284
		>50K		<=50K

Error sum for iteration 99000 = 56.50983433194492

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7638005074022579	-0.705188593681242	age
Hidden Weights:
	-0.8328483827386249	1.0153812944852394
	0.33150371189689015	-0.5965725960973476
		>50K		<=50K

Error sum for iteration 99100 = 56.509834326332346

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.76385590429598	-0.7052313353580664	age
Hidden Weights:
	-0.8328475459932517	1.0153804577050407
	0.33150115902548183	-0.5965700432224393
		>50K		<=50K

Error sum for iteration 99200 = 56.50983432073044

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7639112457057999	-0.7052740435607573	age
Hidden Weights:
	-0.8328467100807189	1.0153796217577518
	0.33149860812698995	-0.5965674923205381
		>50K		<=50K

Error sum for iteration 99300 = 56.509834315139045

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7639665317431727	-0.7053167183418976	age
Hidden Weights:
	-0.8328458749993846	1.0153787866417063
	0.331496059198358	-0.5965649433884784
		>50K		<=50K

Error sum for iteration 99400 = 56.509834309558315

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7640217625191028	-0.7053593597538964	age
Hidden Weights:
	-0.8328450407475686	1.015377952355236
	0.331493512236533	-0.596562396423191
		>50K		<=50K

Error sum for iteration 99500 = 56.50983430398806

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7640769381442839	-0.7054019678491263	age
Hidden Weights:
	-0.8328442073236173	1.0153771188966996
	0.33149096723847016	-0.5965598514216492
		>50K		<=50K

Error sum for iteration 99600 = 56.509834298428295

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7641320587290816	-0.705444542679734	age
Hidden Weights:
	-0.8328433747258854	1.015376286264442
	0.3314884242010807	-0.5965573083808346
		>50K		<=50K

Error sum for iteration 99700 = 56.50983429287912

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7641871243834996	-0.7054870842978607	age
Hidden Weights:
	-0.832842542952727	1.0153754544568063
	0.33148588312131017	-0.5965547672976513
		>50K		<=50K

Error sum for iteration 99800 = 56.50983428734034

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7642421352172875	-0.7055295927554708	age
Hidden Weights:
	-0.832841712002499	1.0153746234721712
	0.33148334399612295	-0.596552228169029
		>50K		<=50K

Error sum for iteration 99900 = 56.50983428181198

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7642970913397892	-0.7055720681043715	age
Hidden Weights:
	-0.8328408818735594	1.015373793308878
	0.33148080682249975	-0.5965496909919829
		>50K		<=50K


Options: -I 100000 

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	100000
	-E	0.01
	-S	1624046435
	-H	2
	-M	0.01
Input Weights:
	0.7643514441147112	-0.7056140861367931	age
Hidden Weights:
	-0.8328400608533283	1.0153729722546878
	0.3314782969400359	-0.5965471811061515
		>50K		<=50K



=== Error on training data ===

Correctly Classified Instances         387               77.4    %
Incorrectly Classified Instances       113               22.6    %
Mean absolute error                      0.3793
Root mean squared error                  0.4217
Relative absolute error                108.2367 %
Root relative squared error            100.8225 %
Total Number of Instances              500     


=== Confusion Matrix ===

   a   b   <-- classified as
   0 113 |   a = >50K
   0 387 |   b = <=50K


=== Error on test data ===

Correctly Classified Instances         385               76.8463 %
Incorrectly Classified Instances       116               23.1537 %
Mean absolute error                      0.3818
Root mean squared error                  0.4246
Relative absolute error                108.0012 %
Root relative squared error            100.6459 %
Total Number of Instances              501     


=== Confusion Matrix ===

   a   b   <-- classified as
   0 116 |   a = >50K
   0 385 |   b = <=50K

by: Keith A. Pray
Last Modified: July 4, 2004 9:05 AM
© 2004 - 1975 Keith A. Pray.
All rights reserved.

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