Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 2000 -E 0.01 -S 1623219896 -H 2 -M 0.01 Input Weights: -0.32048888500310957 0.03934822434544061 age Hidden Weights: -0.743397141457063 0.8293823345580009 0.20298606102141492 -0.21788696895113957 >50K <=50K Error sum for iteration 100 = 59.25125929109509 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 2000 -E 0.01 -S 1623219896 -H 2 -M 0.01 Input Weights: -0.034204533626444385 -0.2789663502963451 age Hidden Weights: -0.8325842400166106 0.9170487962445274 0.14251523337474545 -0.18978799901672758 >50K <=50K Error sum for iteration 201 = 60.446700449418294 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 2000 -E 0.01 -S 1623219896 -H 2 -M 0.01 Input Weights: -0.04065576030064921 -0.3083022554022436 age Hidden Weights: -1.098812457328804 1.1791256834185373 0.13792039437924947 -0.1852364783526837 >50K <=50K Error sum for iteration 302 = 61.88792155197696 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 2000 -E 0.01 -S 1623219896 -H 2 -M 0.01 Input Weights: -0.05314052476022916 -0.32507597126935384 age Hidden Weights: -1.404808442999115 1.4781171230354293 0.13521804319536884 -0.18256873293259904 >50K <=50K Error sum for iteration 403 = 63.177179801146494 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 2000 -E 0.01 -S 1623219896 -H 2 -M 0.01 Input Weights: -0.07244985041060645 -0.33572998633577583 age Hidden Weights: -1.7394330264807945 1.801944329584247 0.13347452898483567 -0.1808560052800573 >50K <=50K Error sum for iteration 504 = 63.72704065796363 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 2000 -E 0.01 -S 1623219896 -H 2 -M 0.01 Input Weights: -0.09672877345143953 -0.3424051069283436 age Hidden Weights: -2.063459635683654 2.1129078851839433 0.13237756234980577 -0.17978416689858032 >50K <=50K Error sum for iteration 605 = 63.574205578551734 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 2000 -E 0.01 -S 1623219896 -H 2 -M 0.01 Input Weights: -0.12134909891477626 -0.34647096887626033 age Hidden Weights: -2.3360462866945353 2.3733816155224794 0.13171522726618096 -0.17913933019210337 >50K <=50K Error sum for iteration 706 = 63.1848098708934 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 2000 -E 0.01 -S 1623219896 -H 2 -M 0.01 Input Weights: -0.14198984253287583 -0.34897039343442676 age Hidden Weights: -2.547721625223744 2.575652024848619 0.13131675714923732 -0.17875185457925574 >50K <=50K Error sum for iteration 807 = 62.82518766306001 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 2000 -E 0.01 -S 1623219896 -H 2 -M 0.01 Input Weights: -0.15790862953956342 -0.3505582663187754 age Hidden Weights: -2.706443155664248 2.727582498686221 0.1310720117904879 -0.17851385930331293 >50K <=50K Error sum for iteration 908 = 62.55095050134649 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 2000 -E 0.01 -S 1623219896 -H 2 -M 0.01 Input Weights: -0.17094230904366223 -0.3516076382527103 age Hidden Weights: -2.8234205582884084 2.8397135623695036 0.1309176814006914 -0.17836376750944577 >50K <=50K Error sum for iteration 1009 = 62.33328118147873 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 2000 -E 0.01 -S 1623219896 -H 2 -M 0.01 Input Weights: -0.18217344791040838 -0.3523263999957532 age Hidden Weights: -2.90927208239162 2.922055332686004 0.13081849858913652 -0.17826735124141657 >50K <=50K Error sum for iteration 1110 = 62.15460666609947 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 2000 -E 0.01 -S 1623219896 -H 2 -M 0.01 Input Weights: -0.1920205193329269 -0.3528317060678578 age Hidden Weights: -2.9722664745390532 2.982449815048388 0.13075466554540752 -0.17820539627026655 >50K <=50K Error sum for iteration 1211 = 62.01990288800556 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 2000 -E 0.01 -S 1623219896 -H 2 -M 0.01 Input Weights: -0.20071101099634578 -0.3531921568516267 age Hidden Weights: -3.0182990575244193 3.026512621766249 0.13071464749811565 -0.1781666979369542 >50K <=50K Error sum for iteration 1312 = 61.91414562012878 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 2000 -E 0.01 -S 1623219896 -H 2 -M 0.01 Input Weights: -0.20841797005219972 -0.353449774167204 age Hidden Weights: -3.0514483422929803 3.0581396231713724 0.13069141498645703 -0.1781444200039638 >50K <=50K Error sum for iteration 1413 = 61.81845859443648 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 2000 -E 0.01 -S 1623219896 -H 2 -M 0.01 Input Weights: -0.21528746946440985 -0.35363144625831994 age Hidden Weights: -3.0745258083487714 3.0800207072844485 0.13068049211887153 -0.17813420435687835 >50K <=50K Error sum for iteration 1514 = 61.73620554827852 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 2000 -E 0.01 -S 1623219896 -H 2 -M 0.01 Input Weights: -0.22144307610174221 -0.3537550944398007 age Hidden Weights: -3.0894965037834945 3.0940378212515642 0.13067890971542365 -0.17813315646809846 >50K <=50K Error sum for iteration 1615 = 61.66473055012075 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 2000 -E 0.01 -S 1623219896 -H 2 -M 0.01 Input Weights: -0.2269878385337108 -0.3538331146897827 age Hidden Weights: -3.097768368481578 3.101540599393318 0.13068462373560585 -0.178139281296009 >50K <=50K Error sum for iteration 1716 = 61.60167704817444 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 2000 -E 0.01 -S 1623219896 -H 2 -M 0.01 Input Weights: -0.2320069714476083 -0.35387436490524815 age Hidden Weights: -3.1003800582928718 3.1035258038846565 0.13069618069831082 -0.17815115850660362 >50K <=50K Error sum for iteration 1817 = 61.54694633964177 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 2000 -E 0.01 -S 1623219896 -H 2 -M 0.01 Input Weights: -0.23657085786517448 -0.35388535409423605 age Hidden Weights: -3.0981202856220738 3.1007514102983196 0.1307125180061718 -0.17816774851493528 >50K <=50K Error sum for iteration 1918 = 61.49817647190738 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 2000 -E 0.01 -S 1623219896 -H 2 -M 0.01 Input Weights: -0.2407378433184977 -0.3538709807858507 age Hidden Weights: -3.0916040343668025 3.093809435582207 0.13073284021631035 -0.17818827221530464 >50K <=50K Options: -I 2000 Back Propagation Neural Network: Numer Input Nodes: 1 Number Hidden Nodes: 2 Number Output Nodes: 2 -I 2000 -E 0.01 -S 1623219896 -H 2 -M 0.01 Input Weights: -0.24382601524793351 -0.35384369652668995 age Hidden Weights: -3.0836370875261694 3.0855533891692377 0.13075160259694724 -0.17820716727720215 >50K <=50K === Error on training data === Correctly Classified Instances 387 77.4 % Incorrectly Classified Instances 113 22.6 % Mean absolute error 0.3416 Root mean squared error 0.401 Relative absolute error 97.4899 % Root relative squared error 95.8896 % 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 0.3376 Root mean squared error 0.4024 Relative absolute error 95.5207 % Root relative squared error 95.3955 % Total Number of Instances 501 === Confusion Matrix === a b <-- classified as 0 116 | a = >50K 0 385 | b = <=50K