Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6345332648088666 0.19369918816974963 age Hidden Weights: -0.07781517514554581 -0.4251916922156478 0.540449281417478 0.46420090890566756 >50K <=50K Error sum for iteration 100 = 56.513502093680614 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6346751302897106 0.41193694070390086 age Hidden Weights: -0.07783911772066719 -0.4251689638924165 -0.6003525658123797 0.6654726708993642 >50K <=50K Error sum for iteration 200 = 56.5113059412998 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.634814182681199 0.4473191540146173 age Hidden Weights: -0.07786112659103503 -0.42514695277344217 -0.5996014915249283 0.6647188768008655 >50K <=50K Error sum for iteration 300 = 56.51055752669428 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6349528128077607 0.4682344123464627 age Hidden Weights: -0.07788307242634224 -0.42512500543709925 -0.599157493035763 0.6642739656775116 >50K <=50K Error sum for iteration 400 = 56.51017925216285 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6350910514992237 0.4831590895595532 age Hidden Weights: -0.0779049597285495 -0.4251031169597055 -0.5988401449131501 0.6639561573259437 >50K <=50K Error sum for iteration 500 = 56.50995066830963 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6352289102746236 0.4947807435544182 age Hidden Weights: -0.07792679018082518 -0.42508128551792934 -0.5985926158676961 0.6637083498192692 >50K <=50K Error sum for iteration 600 = 56.50979747245249 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.63536639548737 0.5043042193954129 age Hidden Weights: -0.07794856471178652 -0.42505951011847154 -0.5983894667044216 0.6635050134987713 >50K <=50K Error sum for iteration 700 = 56.50968758705165 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6355035114809121 0.5123750746537693 age Hidden Weights: -0.07797028395634052 -0.4250377900910079 -0.5982170696661259 0.6633324817071641 >50K <=50K Error sum for iteration 800 = 56.509604886033216 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6356402616417167 0.5193799488944785 age Hidden Weights: -0.07799194840951963 -0.4250161249189629 -0.5980672603251975 0.6631825705014719 >50K <=50K Error sum for iteration 900 = 56.509540371786386 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6357766488363717 0.525568907379613 age Hidden Weights: -0.07801355849036105 -0.4249945141691179 -0.5979347555432021 0.6630499858663529 >50K <=50K Error sum for iteration 1000 = 56.509488626462456 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6359126756209362 0.5311130776185103 age Hidden Weights: -0.07803511457250595 -0.42497295745804414 -0.5978159377638275 0.6629311036992429 >50K <=50K Error sum for iteration 1100 = 56.50944619185219 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.636048344351578 0.5361347529564362 age Hidden Weights: -0.07805661700037894 -0.4249514544342287 -0.5977082201510685 0.6628233329861838 >50K <=50K Error sum for iteration 1200 = 56.50941075638143 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6361836572478508 0.5407243818345703 age Hidden Weights: -0.0780780660984521 -0.4249300047679081 -0.5976096882741754 0.6627247565033507 >50K <=50K Error sum for iteration 1300 = 56.50938071598468 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6363186164311371 0.5449507538110454 age Hidden Weights: -0.07809946217686307 -0.42490860814487974 -0.5975188852340519 0.6626339154128524 >50K <=50K Error sum for iteration 1400 = 56.509354922499135 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6364532239489995 0.5488674112256671 age Hidden Weights: -0.07812080553498316 -0.42488726426258555 -0.5974346763713312 0.6625496736669654 >50K <=50K Error sum for iteration 1500 = 56.50933253234167 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6365874817914219 0.5525168500049005 age Hidden Weights: -0.07814209646377863 -0.4248659728275454 -0.5973561605963468 0.6624711291553836 >50K <=50K Error sum for iteration 1600 = 56.509312911728934 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6367213919018401 0.5559333659255641 age Hidden Weights: -0.07816333524744257 -0.4248447335534961 -0.5972826102889719 0.6623975534907305 >50K <=50K Error sum for iteration 1700 = 56.509295575231306 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.636854956184977 0.5591450389926379 age Hidden Weights: -0.07818452216453811 -0.4248235461601527 -0.5972134293819453 0.6623283500176839 >50K <=50K Error sum for iteration 1800 = 56.509280144735925 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6369881765126024 0.5621751513983213 age Hidden Weights: -0.07820565748882835 -0.4248024103723215 -0.5971481233974262 0.6622630238000095 >50K <=50K Error sum for iteration 1900 = 56.50926632132385 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6371210547275801 0.5650432226953362 age Hidden Weights: -0.07822674148988361 -0.424781325919247 -0.5970862775638839 0.6622011597035359 >50K <=50K Error sum for iteration 2000 = 56.50925386555334 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6372535926471592 0.5677657798947405 age Hidden Weights: -0.07824777443354916 -0.42476029253406516 -0.5970275405303951 0.6621424060865989 >50K <=50K Error sum for iteration 2100 = 56.509242583357604 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6373857920653793 0.5703569400109834 age Hidden Weights: -0.07826875658230874 -0.4247393099534077 -0.5969716120425542 0.6620864624590056 >50K <=50K Error sum for iteration 2200 = 56.50923231577551 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6375176547549883 0.5728288573466859 age Hidden Weights: -0.07828968819556423 -0.42471837791711226 -0.5969182334764137 0.6620330700034667 >50K <=50K Error sum for iteration 2300 = 56.50922293135037 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6376491824689762 0.5751920715482083 age Hidden Weights: -0.07831056952984804 -0.4246974961679957 -0.5968671804696828 0.661982004197669 >50K <=50K Error sum for iteration 2400 = 56.50921432042439 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6377803769417809 0.5774557817379682 age Hidden Weights: -0.07833140083901236 -0.42467666445162 -0.5968182571159236 0.6619330690016044 >50K <=50K Error sum for iteration 2500 = 56.509206390796166 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6379112398903569 0.5796280648046431 age Hidden Weights: -0.07835218237437548 -0.4246558825161713 -0.5967712913398551 0.661886092227539 >50K <=50K Error sum for iteration 2600 = 56.509199064377675 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6380417730150233 0.5817160509727385 age Hidden Weights: -0.07837291438483926 -0.4246351501122725 -0.5967261311763918 0.6618409218150855 >50K <=50K Error sum for iteration 2700 = 56.509192274591406 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6381719780000306 0.5837260663108197 age Hidden Weights: -0.07839359711700593 -0.42461446699288896 -0.5966826417493726 0.6617974228067703 >50K <=50K Error sum for iteration 2800 = 56.509185964323216 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6383018565143457 0.5856637493811723 age Hidden Weights: -0.07841423081525374 -0.42459383291330016 -0.596640702797741 0.6617554748716951 >50K <=50K Error sum for iteration 2900 = 56.50918008429717 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6384314102120262 0.5875341474663378 age Hidden Weights: -0.0784348157218135 -0.4245732476309589 -0.5966002066341503 0.6617149702622053 >50K <=50K Error sum for iteration 3000 = 56.509174591774716 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.638560640732785 0.58934179652025 age Hidden Weights: -0.07845535207684226 -0.42455271090540847 -0.5965610564483395 0.6616758121156923 >50K <=50K Error sum for iteration 3100 = 56.509169449504526 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6386895497023756 0.591090788040187 age Hidden Weights: -0.07847584011847021 -0.4245322224982644 -0.5965231648875988 0.6616379130337685 >50K <=50K Error sum for iteration 3200 = 56.50916462486848 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6388181387328268 0.5927848253468606 age Hidden Weights: -0.0784962800828558 -0.424511782173095 -0.5964864528617746 0.6616011938862355 >50K <=50K Error sum for iteration 3300 = 56.509160089182515 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6389464094228509 0.5944272712249152 age Hidden Weights: -0.0785166722042455 -0.42449138969544703 -0.5964508485313512 0.6615655827983312 >50K <=50K Error sum for iteration 3400 = 56.50915581712028 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6390743633581961 0.596021188468345 age Hidden Weights: -0.07853701671498486 -0.4244710448327772 -0.5964162864460525 0.6615310142886487 >50K <=50K Error sum for iteration 3500 = 56.509151786235876 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6392020021117936 0.5975693745627326 age Hidden Weights: -0.07855731384559195 -0.42445074735438754 -0.5963827068077928 0.6614974285314564 >50K <=50K Error sum for iteration 3600 = 56.50914797656459 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6393293272440862 0.5990743914935596 age Hidden Weights: -0.07857756382476738 -0.42443049703140506 -0.5963500548370233 0.6614647707226066 >50K <=50K Error sum for iteration 3700 = 56.50914437028989 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6394563403031057 0.6005385914803747 age Hidden Weights: -0.07859776687943469 -0.42441029363669797 -0.5963182802255279 0.6614329905319007 >50K <=50K Error sum for iteration 3800 = 56.50914095146109 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6395830428248244 0.6019641392873487 age Hidden Weights: -0.07861792323476305 -0.42439013694496885 -0.5962873366619261 0.6614020416282879 >50K <=50K Error sum for iteration 3900 = 56.509137705755535 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6397094363333375 0.6033530316430089 age Hidden Weights: -0.07863803311420887 -0.4243700267326524 -0.5962571814185607 0.6613718812663794 >50K <=50K Error sum for iteration 4000 = 56.509134620275866 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6398355223409408 0.6047071142073037 age Hidden Weights: -0.07865809673953611 -0.4243499627778588 -0.5962277749903927 0.6613424699251798 >50K <=50K Error sum for iteration 4100 = 56.50913168337659 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6399613023484282 0.6060280964488061 age Hidden Weights: -0.07867811433083188 -0.42432994486037323 -0.596199080778435 0.661313770991271 >50K <=50K Error sum for iteration 4200 = 56.5091288845161 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6400867778451348 0.6073175647335588 age Hidden Weights: -0.0786980861065369 -0.42430997276163396 -0.596171064811003 0.6612857504799166 >50K <=50K Error sum for iteration 4300 = 56.50912621412837 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6402119503091916 0.6085769938775437 age Hidden Weights: -0.0787180122834755 -0.42429004626470695 -0.5961436954977889 0.6612583767889139 >50K <=50K Error sum for iteration 4400 = 56.509123663513066 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6403368212075714 0.6098077573744765 age Hidden Weights: -0.07873789307686277 -0.42427016515428023 -0.5961169434119953 0.6612316204806549 >50K <=50K Error sum for iteration 4500 = 56.509121224739395 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.640461391996355 0.6110111364769135 age Hidden Weights: -0.07875772870033035 -0.42425032921663464 -0.5960907810968606 0.6612054540885204 >50K <=50K Error sum for iteration 4600 = 56.50911889056245 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6405856641207962 0.6121883282818337 age Hidden Weights: -0.0787775193659532 -0.42423053823964313 -0.5960651828933764 0.6611798519444758 >50K <=50K Error sum for iteration 4700 = 56.50911665435106 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6407096390154069 0.613340452948809 age Hidden Weights: -0.07879726528425603 -0.4242107920126849 -0.5960401247864545 0.6611547900251538 >50K <=50K Error sum for iteration 4800 = 56.509114510024304 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6408333181041951 0.6144685601600859 age Hidden Weights: -0.07881696666424254 -0.42419109032665747 -0.5960155842671914 0.6611302458140655 >50K <=50K Error sum for iteration 4900 = 56.50911245199475 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6409567028007003 0.6155736349163144 age Hidden Weights: -0.07883662371340479 -0.42417143297401166 -0.595991540209324 0.6611061981779575 >50K <=50K Error sum for iteration 5000 = 56.50911047512011 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6410797945081967 0.6166566027480795 age Hidden Weights: -0.07885623663774222 -0.4241518197486705 -0.5959679727580481 0.6610826272556105 >50K <=50K Error sum for iteration 5100 = 56.509108574659344 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6412025946196389 0.6177183344128105 age Hidden Weights: -0.07887580564178326 -0.4241322504460677 -0.5959448632298722 0.6610595143575736 >50K <=50K Error sum for iteration 5200 = 56.5091067462344 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6413251045179461 0.6187596501366014 age Hidden Weights: -0.07889533092859868 -0.4241127248630697 -0.5959221940221004 0.6610368418756628 >50K <=50K Error sum for iteration 5300 = 56.509104985795716 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6414473255760467 0.6197813234530447 age Hidden Weights: -0.07891481269981009 -0.42409324279797206 -0.5958999485309124 0.6610145932009684 >50K <=50K Error sum for iteration 5400 = 56.50910328959265 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6415692591570291 0.6207840846841374 age Hidden Weights: -0.07893425115562326 -0.42407380405050576 -0.5958781110770796 0.6609927526495509 >50K <=50K Error sum for iteration 5500 = 56.509101654145944 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6416909066142211 0.6217686241025944 age Hidden Weights: -0.07895364649481913 -0.42405440842185954 -0.5958566668384563 0.6609713053948738 >50K <=50K Error sum for iteration 5600 = 56.50910007622331 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6418122692911975 0.6227355948099356 age Hidden Weights: -0.0789729989147939 -0.42403505571458644 -0.5958356017885275 0.6609502374063682 >50K <=50K Error sum for iteration 5700 = 56.50909855281854 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6419333485220199 0.623685615360412 age Hidden Weights: -0.07899230861154527 -0.42401574573264517 -0.5958149026403897 0.660929535393327 >50K <=50K Error sum for iteration 5800 = 56.50909708113168 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6420541456313336 0.6246192721573455 age Hidden Weights: -0.07901157577971765 -0.42399647828135384 -0.59579455679556 0.6609091867537162 >50K <=50K Error sum for iteration 5900 = 56.50909565855143 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6421746619343424 0.6255371216451558 age Hidden Weights: -0.07903080061259556 -0.4239772531673432 -0.5957745522971674 0.6608891795273611 >50K <=50K Error sum for iteration 6000 = 56.50909428264027 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6422948987369814 0.6264396923175396 age Hidden Weights: -0.07904998330211548 -0.4239580701986619 -0.5957548777870031 0.6608695023529775 >50K <=50K Error sum for iteration 6100 = 56.50909295111889 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6424148573360591 0.6273274865602121 age Hidden Weights: -0.07906912403889232 -0.42393892918464027 -0.5957355224661963 0.6608501444288019 >50K <=50K Error sum for iteration 6200 = 56.50909166185502 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6425345390192382 0.6282009823439513 age Hidden Weights: -0.07908822301222591 -0.4239198299359619 -0.5957164760590089 0.6608310954763775 >50K <=50K Error sum for iteration 6300 = 56.509090412851094 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6426539450651848 0.6290606347827948 age Hidden Weights: -0.07910728041010778 -0.4239007722645905 -0.5956977287795053 0.6608123457072254 >50K <=50K Error sum for iteration 6400 = 56.50908920223345 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6427730767436665 0.6299068775695403 age Hidden Weights: -0.0791262964192425 -0.42388175598377037 -0.5956792713009021 0.6607938857921867 >50K <=50K Error sum for iteration 6500 = 56.50908802824315 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6428919353155474 0.6307401243004994 age Hidden Weights: -0.07914527122506221 -0.4238627809080786 -0.5956610947272145 0.660775706833019 >50K <=50K Error sum for iteration 6600 = 56.50908688922776 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6430105220330895 0.6315607696991646 age Hidden Weights: -0.07916420501173312 -0.4238438468532761 -0.5956431905670844 0.6607578003362597 >50K <=50K Error sum for iteration 6700 = 56.5090857836325 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6431288381398167 0.6323691907481879 age Hidden Weights: -0.07918309796217184 -0.4238249536364555 -0.5956255507096109 0.6607401581890086 >50K <=50K Error sum for iteration 6800 = 56.5090847099941 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6432468848706576 0.6331657477376732 age Hidden Weights: -0.07920195025804262 -0.4238061010758897 -0.5956081674018614 0.6607227726364663 >50K <=50K Error sum for iteration 6900 = 56.50908366693321 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6433646634520442 0.6339507852370824 age Hidden Weights: -0.0792207620797853 -0.42378728899112145 -0.5955910332281121 0.6607056362611465 >50K <=50K Error sum for iteration 7000 = 56.50908265314928 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.643482175102075 0.6347246329975111 age Hidden Weights: -0.07923953360662882 -0.42376851720289854 -0.5955741410905486 0.6606887419635548 >50K <=50K Error sum for iteration 7100 = 56.509081667414634 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6435994210304902 0.6354876067899737 age Hidden Weights: -0.07925826501659003 -0.4237497855331638 -0.5955574841913172 0.6606720829442392 >50K <=50K Error sum for iteration 7200 = 56.50908070856923 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6437164024387634 0.6362400091853065 age Hidden Weights: -0.07927695648648712 -0.4237310938050754 -0.5955410560158013 0.6606556526871129 >50K <=50K Error sum for iteration 7300 = 56.5090797755165 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6438331205201382 0.6369821302803863 age Hidden Weights: -0.07929560819196567 -0.4237124418429435 -0.5955248503171277 0.660639444943886 >50K <=50K Error sum for iteration 7400 = 56.5090788672188 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.643949576459883 0.6377142483749841 age Hidden Weights: -0.07931422030749118 -0.42369382947233947 -0.595508861101626 0.6606234537195365 >50K <=50K Error sum for iteration 7500 = 56.50907798269341 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6440657714350977 0.6384366306034209 age Hidden Weights: -0.07933279300636123 -0.42367525651987864 -0.5954930826153386 0.660607673258836 >50K <=50K Error sum for iteration 7600 = 56.50907712100936 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6441817066149882 0.6391495335244177 age Hidden Weights: -0.07935132646073455 -0.4236567228134045 -0.5954775093313834 0.6605920980336903 >50K <=50K Error sum for iteration 7700 = 56.50907628128358 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.644297383160937 0.6398532036725034 age Hidden Weights: -0.0793698208416197 -0.42363822818188934 -0.5954621359381016 0.6605767227313044 >50K <=50K Error sum for iteration 7800 = 56.50907546267816 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6444128022264501 0.6405478780739052 age Hidden Weights: -0.07938827631888837 -0.42361977245544513 -0.5954469573280912 0.6605615422431645 >50K <=50K Error sum for iteration 7900 = 56.50907466439729 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6445279649573786 0.6412337847297019 age Hidden Weights: -0.07940669306131161 -0.42360135546527355 -0.5954319685877455 0.6605465516546404 >50K <=50K Error sum for iteration 8000 = 56.50907388568488 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6446428724917859 0.6419111430685581 age Hidden Weights: -0.07942507123653253 -0.4235829770437093 -0.5954171649876313 0.6605317462353091 >50K <=50K Error sum for iteration 8100 = 56.50907312582201 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6447575259602154 0.642580164371585 age Hidden Weights: -0.07944341101109105 -0.42356463702417596 -0.5954025419733658 0.6605171214298522 >50K <=50K Error sum for iteration 8200 = 56.50907238412459 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6448719264857022 0.6432410521710334 age Hidden Weights: -0.07946171255045013 -0.42354633524121854 -0.595388095157071 0.6605026728494878 >50K <=50K Error sum for iteration 8300 = 56.509071659941256 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6449860751837841 0.6438940026249024 age Hidden Weights: -0.07947997601898713 -0.42352807153042543 -0.5953738203093288 0.6604883962639476 >50K <=50K Error sum for iteration 8400 = 56.509070952651555 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6450999731626461 0.6445392048692611 age Hidden Weights: -0.07949820158000477 -0.4235098457284983 -0.5953597133516443 0.6604742875939136 >50K <=50K Error sum for iteration 8500 = 56.509070261664306 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6452136215231221 0.6451768413496778 age Hidden Weights: -0.07951638939575309 -0.42349165767314556 -0.5953457703493468 0.6604603429039361 >50K <=50K Error sum for iteration 8600 = 56.50906958641538 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6453270213587883 0.6458070881333201 age Hidden Weights: -0.07953453962741462 -0.4234735072032088 -0.5953319875048604 0.6604465583957012 >50K <=50K Error sum for iteration 8700 = 56.50906892636651 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.645440173756012 0.6464301152031734 age Hidden Weights: -0.07955265243513884 -0.42345539415846967 -0.5953183611514359 0.6604329304017484 >50K <=50K Error sum for iteration 8800 = 56.509068281003906 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6455530797940531 0.6470460867353296 age Hidden Weights: -0.07957072797803814 -0.42343731837981363 -0.5953048877471881 0.6604194553795014 >50K <=50K Error sum for iteration 8900 = 56.509067649836794 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6456657405451331 0.6476551613606347 age Hidden Weights: -0.07958876641419749 -0.42341927970913973 -0.5952915638694665 0.660406129905668 >50K <=50K Error sum for iteration 9000 = 56.5090670323957 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6457781570743348 0.6482574924119288 age Hidden Weights: -0.07960676790068816 -0.42340127798938454 -0.5952783862095864 0.6603929506709283 >50K <=50K Error sum for iteration 9100 = 56.50906642823222 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6458903304399362 0.6488532281575514 age Hidden Weights: -0.0796247325935777 -0.4233833130644554 -0.5952653515677818 0.6603799144749306 >50K <=50K Error sum for iteration 9200 = 56.50906583691702 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6460022616933218 0.6494425120221067 age Hidden Weights: -0.07964266064793156 -0.4233653847792617 -0.5952524568484948 0.6603670182215288 >50K <=50K Error sum for iteration 9300 = 56.50906525803926 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.646113951879041 0.6500254827953242 age Hidden Weights: -0.07966055221782235 -0.42334749297970836 -0.5952396990558807 0.6603542589143389 >50K <=50K Error sum for iteration 9400 = 56.50906469120535 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6462254020348339 0.6506022748297354 age Hidden Weights: -0.0796784074563453 -0.4233296375127058 -0.5952270752895665 0.6603416336524605 >50K <=50K Error sum for iteration 9500 = 56.509064136038276 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6463366131917556 0.6511730182280804 age Hidden Weights: -0.07969622651561305 -0.4233118182261373 -0.5952145827406377 0.6603291396264713 >50K <=50K Error sum for iteration 9600 = 56.50906359217684 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6464475863741969 0.6517378390207297 age Hidden Weights: -0.07971400954678895 -0.42329403496878876 -0.5952022186877982 0.6603167741146079 >50K <=50K Error sum for iteration 9700 = 56.50906305927436 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6465583226000714 0.6522968593340495 age Hidden Weights: -0.0797317567000767 -0.4232762875904732 -0.5951899804938195 0.6603045344791463 >50K <=50K Error sum for iteration 9800 = 56.50906253699831 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.646668822880635 0.6528501975501165 age Hidden Weights: -0.07974946812472058 -0.4232585759419144 -0.5951778656020511 0.6602924181629893 >50K <=50K Error sum for iteration 9900 = 56.509062025029536 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6467790882206429 0.6533979684583469 age Hidden Weights: -0.07976714396903443 -0.42324089987483243 -0.5951658715331722 0.6602804226863951 >50K <=50K Options: -I 10000 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 10000 -E 0.01 -S 1623907097 -H 2 -M 0.01 Input Weights: -0.6468880204592897 0.6539348868997474 age Hidden Weights: -0.07978460815119777 -0.4232234354731941 -0.5951541140601907 0.6602686638357838 >50K <=50K === Error on training data === Correctly Classified Instances 387 77.4 % Incorrectly Classified Instances 113 22.6 % Mean absolute error 0.3803 Root mean squared error 0.4219 Relative absolute error 108.5157 % Root relative squared error 100.8778 % Total Number of Instances 500 === Confusion Matrix === a b <-- classified as 0 113 | a = >50K 0 387 | b = <=50K === Error on test data === Correctly Classified Instances 385 76.8463 % Incorrectly Classified Instances 116 23.1537 % Mean absolute error 0.3827 Root mean squared error 0.4248 Relative absolute error 108.2723 % Root relative squared error 100.6949 % Total Number of Instances 501 === Confusion Matrix === a b <-- classified as 0 116 | a = >50K 0 385 | b = <=50K