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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	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6345332648088666	0.19369918816974963	age
Hidden Weights:
	-0.07781517514554581	-0.4251916922156478
	0.540449281417478	0.46420090890566756
		>50K		<=50K

Error sum for iteration 100 = 56.513502093680614

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6346751302897106	0.41193694070390086	age
Hidden Weights:
	-0.07783911772066719	-0.4251689638924165
	-0.6003525658123797	0.6654726708993642
		>50K		<=50K

Error sum for iteration 200 = 56.5113059412998

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.634814182681199	0.4473191540146173	age
Hidden Weights:
	-0.07786112659103503	-0.42514695277344217
	-0.5996014915249283	0.6647188768008655
		>50K		<=50K

Error sum for iteration 300 = 56.51055752669428

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6349528128077607	0.4682344123464627	age
Hidden Weights:
	-0.07788307242634224	-0.42512500543709925
	-0.599157493035763	0.6642739656775116
		>50K		<=50K

Error sum for iteration 400 = 56.51017925216285

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6350910514992237	0.4831590895595532	age
Hidden Weights:
	-0.0779049597285495	-0.4251031169597055
	-0.5988401449131501	0.6639561573259437
		>50K		<=50K

Error sum for iteration 500 = 56.50995066830963

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6352289102746236	0.4947807435544182	age
Hidden Weights:
	-0.07792679018082518	-0.42508128551792934
	-0.5985926158676961	0.6637083498192692
		>50K		<=50K

Error sum for iteration 600 = 56.50979747245249

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.63536639548737	0.5043042193954129	age
Hidden Weights:
	-0.07794856471178652	-0.42505951011847154
	-0.5983894667044216	0.6635050134987713
		>50K		<=50K

Error sum for iteration 700 = 56.50968758705165

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6355035114809121	0.5123750746537693	age
Hidden Weights:
	-0.07797028395634052	-0.4250377900910079
	-0.5982170696661259	0.6633324817071641
		>50K		<=50K

Error sum for iteration 800 = 56.509604886033216

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6356402616417167	0.5193799488944785	age
Hidden Weights:
	-0.07799194840951963	-0.4250161249189629
	-0.5980672603251975	0.6631825705014719
		>50K		<=50K

Error sum for iteration 900 = 56.509540371786386

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6357766488363717	0.525568907379613	age
Hidden Weights:
	-0.07801355849036105	-0.4249945141691179
	-0.5979347555432021	0.6630499858663529
		>50K		<=50K

Error sum for iteration 1000 = 56.509488626462456

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6359126756209362	0.5311130776185103	age
Hidden Weights:
	-0.07803511457250595	-0.42497295745804414
	-0.5978159377638275	0.6629311036992429
		>50K		<=50K

Error sum for iteration 1100 = 56.50944619185219

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.636048344351578	0.5361347529564362	age
Hidden Weights:
	-0.07805661700037894	-0.4249514544342287
	-0.5977082201510685	0.6628233329861838
		>50K		<=50K

Error sum for iteration 1200 = 56.50941075638143

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6361836572478508	0.5407243818345703	age
Hidden Weights:
	-0.0780780660984521	-0.4249300047679081
	-0.5976096882741754	0.6627247565033507
		>50K		<=50K

Error sum for iteration 1300 = 56.50938071598468

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6363186164311371	0.5449507538110454	age
Hidden Weights:
	-0.07809946217686307	-0.42490860814487974
	-0.5975188852340519	0.6626339154128524
		>50K		<=50K

Error sum for iteration 1400 = 56.509354922499135

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6364532239489995	0.5488674112256671	age
Hidden Weights:
	-0.07812080553498316	-0.42488726426258555
	-0.5974346763713312	0.6625496736669654
		>50K		<=50K

Error sum for iteration 1500 = 56.50933253234167

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6365874817914219	0.5525168500049005	age
Hidden Weights:
	-0.07814209646377863	-0.4248659728275454
	-0.5973561605963468	0.6624711291553836
		>50K		<=50K

Error sum for iteration 1600 = 56.509312911728934

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6367213919018401	0.5559333659255641	age
Hidden Weights:
	-0.07816333524744257	-0.4248447335534961
	-0.5972826102889719	0.6623975534907305
		>50K		<=50K

Error sum for iteration 1700 = 56.509295575231306

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.636854956184977	0.5591450389926379	age
Hidden Weights:
	-0.07818452216453811	-0.4248235461601527
	-0.5972134293819453	0.6623283500176839
		>50K		<=50K

Error sum for iteration 1800 = 56.509280144735925

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6369881765126024	0.5621751513983213	age
Hidden Weights:
	-0.07820565748882835	-0.4248024103723215
	-0.5971481233974262	0.6622630238000095
		>50K		<=50K

Error sum for iteration 1900 = 56.50926632132385

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6371210547275801	0.5650432226953362	age
Hidden Weights:
	-0.07822674148988361	-0.424781325919247
	-0.5970862775638839	0.6622011597035359
		>50K		<=50K

Error sum for iteration 2000 = 56.50925386555334

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6372535926471592	0.5677657798947405	age
Hidden Weights:
	-0.07824777443354916	-0.42476029253406516
	-0.5970275405303951	0.6621424060865989
		>50K		<=50K

Error sum for iteration 2100 = 56.509242583357604

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6373857920653793	0.5703569400109834	age
Hidden Weights:
	-0.07826875658230874	-0.4247393099534077
	-0.5969716120425542	0.6620864624590056
		>50K		<=50K

Error sum for iteration 2200 = 56.50923231577551

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6375176547549883	0.5728288573466859	age
Hidden Weights:
	-0.07828968819556423	-0.42471837791711226
	-0.5969182334764137	0.6620330700034667
		>50K		<=50K

Error sum for iteration 2300 = 56.50922293135037

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6376491824689762	0.5751920715482083	age
Hidden Weights:
	-0.07831056952984804	-0.4246974961679957
	-0.5968671804696828	0.661982004197669
		>50K		<=50K

Error sum for iteration 2400 = 56.50921432042439

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6377803769417809	0.5774557817379682	age
Hidden Weights:
	-0.07833140083901236	-0.42467666445162
	-0.5968182571159236	0.6619330690016044
		>50K		<=50K

Error sum for iteration 2500 = 56.509206390796166

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6379112398903569	0.5796280648046431	age
Hidden Weights:
	-0.07835218237437548	-0.4246558825161713
	-0.5967712913398551	0.661886092227539
		>50K		<=50K

Error sum for iteration 2600 = 56.509199064377675

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6380417730150233	0.5817160509727385	age
Hidden Weights:
	-0.07837291438483926	-0.4246351501122725
	-0.5967261311763918	0.6618409218150855
		>50K		<=50K

Error sum for iteration 2700 = 56.509192274591406

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6381719780000306	0.5837260663108197	age
Hidden Weights:
	-0.07839359711700593	-0.42461446699288896
	-0.5966826417493726	0.6617974228067703
		>50K		<=50K

Error sum for iteration 2800 = 56.509185964323216

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6383018565143457	0.5856637493811723	age
Hidden Weights:
	-0.07841423081525374	-0.42459383291330016
	-0.596640702797741	0.6617554748716951
		>50K		<=50K

Error sum for iteration 2900 = 56.50918008429717

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6384314102120262	0.5875341474663378	age
Hidden Weights:
	-0.0784348157218135	-0.4245732476309589
	-0.5966002066341503	0.6617149702622053
		>50K		<=50K

Error sum for iteration 3000 = 56.509174591774716

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.638560640732785	0.58934179652025	age
Hidden Weights:
	-0.07845535207684226	-0.42455271090540847
	-0.5965610564483395	0.6616758121156923
		>50K		<=50K

Error sum for iteration 3100 = 56.509169449504526

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6386895497023756	0.591090788040187	age
Hidden Weights:
	-0.07847584011847021	-0.4245322224982644
	-0.5965231648875988	0.6616379130337685
		>50K		<=50K

Error sum for iteration 3200 = 56.50916462486848

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6388181387328268	0.5927848253468606	age
Hidden Weights:
	-0.0784962800828558	-0.424511782173095
	-0.5964864528617746	0.6616011938862355
		>50K		<=50K

Error sum for iteration 3300 = 56.509160089182515

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6389464094228509	0.5944272712249152	age
Hidden Weights:
	-0.0785166722042455	-0.42449138969544703
	-0.5964508485313512	0.6615655827983312
		>50K		<=50K

Error sum for iteration 3400 = 56.50915581712028

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6390743633581961	0.596021188468345	age
Hidden Weights:
	-0.07853701671498486	-0.4244710448327772
	-0.5964162864460525	0.6615310142886487
		>50K		<=50K

Error sum for iteration 3500 = 56.509151786235876

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6392020021117936	0.5975693745627326	age
Hidden Weights:
	-0.07855731384559195	-0.42445074735438754
	-0.5963827068077928	0.6614974285314564
		>50K		<=50K

Error sum for iteration 3600 = 56.50914797656459

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6393293272440862	0.5990743914935596	age
Hidden Weights:
	-0.07857756382476738	-0.42443049703140506
	-0.5963500548370233	0.6614647707226066
		>50K		<=50K

Error sum for iteration 3700 = 56.50914437028989

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6394563403031057	0.6005385914803747	age
Hidden Weights:
	-0.07859776687943469	-0.42441029363669797
	-0.5963182802255279	0.6614329905319007
		>50K		<=50K

Error sum for iteration 3800 = 56.50914095146109

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6395830428248244	0.6019641392873487	age
Hidden Weights:
	-0.07861792323476305	-0.42439013694496885
	-0.5962873366619261	0.6614020416282879
		>50K		<=50K

Error sum for iteration 3900 = 56.509137705755535

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6397094363333375	0.6033530316430089	age
Hidden Weights:
	-0.07863803311420887	-0.4243700267326524
	-0.5962571814185607	0.6613718812663794
		>50K		<=50K

Error sum for iteration 4000 = 56.509134620275866

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6398355223409408	0.6047071142073037	age
Hidden Weights:
	-0.07865809673953611	-0.4243499627778588
	-0.5962277749903927	0.6613424699251798
		>50K		<=50K

Error sum for iteration 4100 = 56.50913168337659

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6399613023484282	0.6060280964488061	age
Hidden Weights:
	-0.07867811433083188	-0.42432994486037323
	-0.596199080778435	0.661313770991271
		>50K		<=50K

Error sum for iteration 4200 = 56.5091288845161

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6400867778451348	0.6073175647335588	age
Hidden Weights:
	-0.0786980861065369	-0.42430997276163396
	-0.596171064811003	0.6612857504799166
		>50K		<=50K

Error sum for iteration 4300 = 56.50912621412837

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6402119503091916	0.6085769938775437	age
Hidden Weights:
	-0.0787180122834755	-0.42429004626470695
	-0.5961436954977889	0.6612583767889139
		>50K		<=50K

Error sum for iteration 4400 = 56.509123663513066

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6403368212075714	0.6098077573744765	age
Hidden Weights:
	-0.07873789307686277	-0.42427016515428023
	-0.5961169434119953	0.6612316204806549
		>50K		<=50K

Error sum for iteration 4500 = 56.509121224739395

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.640461391996355	0.6110111364769135	age
Hidden Weights:
	-0.07875772870033035	-0.42425032921663464
	-0.5960907810968606	0.6612054540885204
		>50K		<=50K

Error sum for iteration 4600 = 56.50911889056245

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6405856641207962	0.6121883282818337	age
Hidden Weights:
	-0.0787775193659532	-0.42423053823964313
	-0.5960651828933764	0.6611798519444758
		>50K		<=50K

Error sum for iteration 4700 = 56.50911665435106

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6407096390154069	0.613340452948809	age
Hidden Weights:
	-0.07879726528425603	-0.4242107920126849
	-0.5960401247864545	0.6611547900251538
		>50K		<=50K

Error sum for iteration 4800 = 56.509114510024304

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6408333181041951	0.6144685601600859	age
Hidden Weights:
	-0.07881696666424254	-0.42419109032665747
	-0.5960155842671914	0.6611302458140655
		>50K		<=50K

Error sum for iteration 4900 = 56.50911245199475

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6409567028007003	0.6155736349163144	age
Hidden Weights:
	-0.07883662371340479	-0.42417143297401166
	-0.595991540209324	0.6611061981779575
		>50K		<=50K

Error sum for iteration 5000 = 56.50911047512011

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6410797945081967	0.6166566027480795	age
Hidden Weights:
	-0.07885623663774222	-0.4241518197486705
	-0.5959679727580481	0.6610826272556105
		>50K		<=50K

Error sum for iteration 5100 = 56.509108574659344

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6412025946196389	0.6177183344128105	age
Hidden Weights:
	-0.07887580564178326	-0.4241322504460677
	-0.5959448632298722	0.6610595143575736
		>50K		<=50K

Error sum for iteration 5200 = 56.5091067462344

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6413251045179461	0.6187596501366014	age
Hidden Weights:
	-0.07889533092859868	-0.4241127248630697
	-0.5959221940221004	0.6610368418756628
		>50K		<=50K

Error sum for iteration 5300 = 56.509104985795716

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6414473255760467	0.6197813234530447	age
Hidden Weights:
	-0.07891481269981009	-0.42409324279797206
	-0.5958999485309124	0.6610145932009684
		>50K		<=50K

Error sum for iteration 5400 = 56.50910328959265

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6415692591570291	0.6207840846841374	age
Hidden Weights:
	-0.07893425115562326	-0.42407380405050576
	-0.5958781110770796	0.6609927526495509
		>50K		<=50K

Error sum for iteration 5500 = 56.509101654145944

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6416909066142211	0.6217686241025944	age
Hidden Weights:
	-0.07895364649481913	-0.42405440842185954
	-0.5958566668384563	0.6609713053948738
		>50K		<=50K

Error sum for iteration 5600 = 56.50910007622331

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6418122692911975	0.6227355948099356	age
Hidden Weights:
	-0.0789729989147939	-0.42403505571458644
	-0.5958356017885275	0.6609502374063682
		>50K		<=50K

Error sum for iteration 5700 = 56.50909855281854

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6419333485220199	0.623685615360412	age
Hidden Weights:
	-0.07899230861154527	-0.42401574573264517
	-0.5958149026403897	0.660929535393327
		>50K		<=50K

Error sum for iteration 5800 = 56.50909708113168

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6420541456313336	0.6246192721573455	age
Hidden Weights:
	-0.07901157577971765	-0.42399647828135384
	-0.59579455679556	0.6609091867537162
		>50K		<=50K

Error sum for iteration 5900 = 56.50909565855143

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6421746619343424	0.6255371216451558	age
Hidden Weights:
	-0.07903080061259556	-0.4239772531673432
	-0.5957745522971674	0.6608891795273611
		>50K		<=50K

Error sum for iteration 6000 = 56.50909428264027

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6422948987369814	0.6264396923175396	age
Hidden Weights:
	-0.07904998330211548	-0.4239580701986619
	-0.5957548777870031	0.6608695023529775
		>50K		<=50K

Error sum for iteration 6100 = 56.50909295111889

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6424148573360591	0.6273274865602121	age
Hidden Weights:
	-0.07906912403889232	-0.42393892918464027
	-0.5957355224661963	0.6608501444288019
		>50K		<=50K

Error sum for iteration 6200 = 56.50909166185502

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6425345390192382	0.6282009823439513	age
Hidden Weights:
	-0.07908822301222591	-0.4239198299359619
	-0.5957164760590089	0.6608310954763775
		>50K		<=50K

Error sum for iteration 6300 = 56.509090412851094

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6426539450651848	0.6290606347827948	age
Hidden Weights:
	-0.07910728041010778	-0.4239007722645905
	-0.5956977287795053	0.6608123457072254
		>50K		<=50K

Error sum for iteration 6400 = 56.50908920223345

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6427730767436665	0.6299068775695403	age
Hidden Weights:
	-0.0791262964192425	-0.42388175598377037
	-0.5956792713009021	0.6607938857921867
		>50K		<=50K

Error sum for iteration 6500 = 56.50908802824315

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6428919353155474	0.6307401243004994	age
Hidden Weights:
	-0.07914527122506221	-0.4238627809080786
	-0.5956610947272145	0.660775706833019
		>50K		<=50K

Error sum for iteration 6600 = 56.50908688922776

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6430105220330895	0.6315607696991646	age
Hidden Weights:
	-0.07916420501173312	-0.4238438468532761
	-0.5956431905670844	0.6607578003362597
		>50K		<=50K

Error sum for iteration 6700 = 56.5090857836325

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6431288381398167	0.6323691907481879	age
Hidden Weights:
	-0.07918309796217184	-0.4238249536364555
	-0.5956255507096109	0.6607401581890086
		>50K		<=50K

Error sum for iteration 6800 = 56.5090847099941

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6432468848706576	0.6331657477376732	age
Hidden Weights:
	-0.07920195025804262	-0.4238061010758897
	-0.5956081674018614	0.6607227726364663
		>50K		<=50K

Error sum for iteration 6900 = 56.50908366693321

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6433646634520442	0.6339507852370824	age
Hidden Weights:
	-0.0792207620797853	-0.42378728899112145
	-0.5955910332281121	0.6607056362611465
		>50K		<=50K

Error sum for iteration 7000 = 56.50908265314928

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.643482175102075	0.6347246329975111	age
Hidden Weights:
	-0.07923953360662882	-0.42376851720289854
	-0.5955741410905486	0.6606887419635548
		>50K		<=50K

Error sum for iteration 7100 = 56.509081667414634

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6435994210304902	0.6354876067899737	age
Hidden Weights:
	-0.07925826501659003	-0.4237497855331638
	-0.5955574841913172	0.6606720829442392
		>50K		<=50K

Error sum for iteration 7200 = 56.50908070856923

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6437164024387634	0.6362400091853065	age
Hidden Weights:
	-0.07927695648648712	-0.4237310938050754
	-0.5955410560158013	0.6606556526871129
		>50K		<=50K

Error sum for iteration 7300 = 56.5090797755165

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6438331205201382	0.6369821302803863	age
Hidden Weights:
	-0.07929560819196567	-0.4237124418429435
	-0.5955248503171277	0.660639444943886
		>50K		<=50K

Error sum for iteration 7400 = 56.5090788672188

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.643949576459883	0.6377142483749841	age
Hidden Weights:
	-0.07931422030749118	-0.42369382947233947
	-0.595508861101626	0.6606234537195365
		>50K		<=50K

Error sum for iteration 7500 = 56.50907798269341

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6440657714350977	0.6384366306034209	age
Hidden Weights:
	-0.07933279300636123	-0.42367525651987864
	-0.5954930826153386	0.660607673258836
		>50K		<=50K

Error sum for iteration 7600 = 56.50907712100936

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6441817066149882	0.6391495335244177	age
Hidden Weights:
	-0.07935132646073455	-0.4236567228134045
	-0.5954775093313834	0.6605920980336903
		>50K		<=50K

Error sum for iteration 7700 = 56.50907628128358

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.644297383160937	0.6398532036725034	age
Hidden Weights:
	-0.0793698208416197	-0.42363822818188934
	-0.5954621359381016	0.6605767227313044
		>50K		<=50K

Error sum for iteration 7800 = 56.50907546267816

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6444128022264501	0.6405478780739052	age
Hidden Weights:
	-0.07938827631888837	-0.42361977245544513
	-0.5954469573280912	0.6605615422431645
		>50K		<=50K

Error sum for iteration 7900 = 56.50907466439729

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6445279649573786	0.6412337847297019	age
Hidden Weights:
	-0.07940669306131161	-0.42360135546527355
	-0.5954319685877455	0.6605465516546404
		>50K		<=50K

Error sum for iteration 8000 = 56.50907388568488

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6446428724917859	0.6419111430685581	age
Hidden Weights:
	-0.07942507123653253	-0.4235829770437093
	-0.5954171649876313	0.6605317462353091
		>50K		<=50K

Error sum for iteration 8100 = 56.50907312582201

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6447575259602154	0.642580164371585	age
Hidden Weights:
	-0.07944341101109105	-0.42356463702417596
	-0.5954025419733658	0.6605171214298522
		>50K		<=50K

Error sum for iteration 8200 = 56.50907238412459

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6448719264857022	0.6432410521710334	age
Hidden Weights:
	-0.07946171255045013	-0.42354633524121854
	-0.595388095157071	0.6605026728494878
		>50K		<=50K

Error sum for iteration 8300 = 56.509071659941256

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6449860751837841	0.6438940026249024	age
Hidden Weights:
	-0.07947997601898713	-0.42352807153042543
	-0.5953738203093288	0.6604883962639476
		>50K		<=50K

Error sum for iteration 8400 = 56.509070952651555

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6450999731626461	0.6445392048692611	age
Hidden Weights:
	-0.07949820158000477	-0.4235098457284983
	-0.5953597133516443	0.6604742875939136
		>50K		<=50K

Error sum for iteration 8500 = 56.509070261664306

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6452136215231221	0.6451768413496778	age
Hidden Weights:
	-0.07951638939575309	-0.42349165767314556
	-0.5953457703493468	0.6604603429039361
		>50K		<=50K

Error sum for iteration 8600 = 56.50906958641538

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6453270213587883	0.6458070881333201	age
Hidden Weights:
	-0.07953453962741462	-0.4234735072032088
	-0.5953319875048604	0.6604465583957012
		>50K		<=50K

Error sum for iteration 8700 = 56.50906892636651

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.645440173756012	0.6464301152031734	age
Hidden Weights:
	-0.07955265243513884	-0.42345539415846967
	-0.5953183611514359	0.6604329304017484
		>50K		<=50K

Error sum for iteration 8800 = 56.509068281003906

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6455530797940531	0.6470460867353296	age
Hidden Weights:
	-0.07957072797803814	-0.42343731837981363
	-0.5953048877471881	0.6604194553795014
		>50K		<=50K

Error sum for iteration 8900 = 56.509067649836794

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6456657405451331	0.6476551613606347	age
Hidden Weights:
	-0.07958876641419749	-0.42341927970913973
	-0.5952915638694665	0.660406129905668
		>50K		<=50K

Error sum for iteration 9000 = 56.5090670323957

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6457781570743348	0.6482574924119288	age
Hidden Weights:
	-0.07960676790068816	-0.42340127798938454
	-0.5952783862095864	0.6603929506709283
		>50K		<=50K

Error sum for iteration 9100 = 56.50906642823222

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6458903304399362	0.6488532281575514	age
Hidden Weights:
	-0.0796247325935777	-0.4233833130644554
	-0.5952653515677818	0.6603799144749306
		>50K		<=50K

Error sum for iteration 9200 = 56.50906583691702

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6460022616933218	0.6494425120221067	age
Hidden Weights:
	-0.07964266064793156	-0.4233653847792617
	-0.5952524568484948	0.6603670182215288
		>50K		<=50K

Error sum for iteration 9300 = 56.50906525803926

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.646113951879041	0.6500254827953242	age
Hidden Weights:
	-0.07966055221782235	-0.42334749297970836
	-0.5952396990558807	0.6603542589143389
		>50K		<=50K

Error sum for iteration 9400 = 56.50906469120535

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6462254020348339	0.6506022748297354	age
Hidden Weights:
	-0.0796784074563453	-0.4233296375127058
	-0.5952270752895665	0.6603416336524605
		>50K		<=50K

Error sum for iteration 9500 = 56.509064136038276

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6463366131917556	0.6511730182280804	age
Hidden Weights:
	-0.07969622651561305	-0.4233118182261373
	-0.5952145827406377	0.6603291396264713
		>50K		<=50K

Error sum for iteration 9600 = 56.50906359217684

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6464475863741969	0.6517378390207297	age
Hidden Weights:
	-0.07971400954678895	-0.42329403496878876
	-0.5952022186877982	0.6603167741146079
		>50K		<=50K

Error sum for iteration 9700 = 56.50906305927436

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6465583226000714	0.6522968593340495	age
Hidden Weights:
	-0.0797317567000767	-0.4232762875904732
	-0.5951899804938195	0.6603045344791463
		>50K		<=50K

Error sum for iteration 9800 = 56.50906253699831

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.646668822880635	0.6528501975501165	age
Hidden Weights:
	-0.07974946812472058	-0.4232585759419144
	-0.5951778656020511	0.6602924181629893
		>50K		<=50K

Error sum for iteration 9900 = 56.509062025029536

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6467790882206429	0.6533979684583469	age
Hidden Weights:
	-0.07976714396903443	-0.42324089987483243
	-0.5951658715331722	0.6602804226863951
		>50K		<=50K


Options: -I 10000 

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	10000
	-E	0.01
	-S	1623907097
	-H	2
	-M	0.01
Input Weights:
	-0.6468880204592897	0.6539348868997474	age
Hidden Weights:
	-0.07978460815119777	-0.4232234354731941
	-0.5951541140601907	0.6602686638357838
		>50K		<=50K



=== Error on training data ===

Correctly Classified Instances         387               77.4    %
Incorrectly Classified Instances       113               22.6    %
Mean absolute error                      0.3803
Root mean squared error                  0.4219
Relative absolute error                108.5157 %
Root relative squared error            100.8778 %
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                      0.3827
Root mean squared error                  0.4248
Relative absolute error                108.2723 %
Root relative squared error            100.6949 %
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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