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Experiments
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
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