Back Propagation Neural Network: Numer Input Nodes: 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