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Experiments
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 100
-E 0.5
-S 113129835
-H 2
-M 0.5
Input Weights:
0.4088222632788374 0.5012578226466649
-0.6625624070969929 0.629252123304938
0.8954233723949854 0.46843741500490266
-0.4151057697338172 0.6951933675740394
-0.5522245020700418 -0.1640491654930072
0.17076623241980915 -0.6980556270081983
0.3120369393547453 0.6283743790724161
-0.745458808868666 -0.3240482107905984
-0.6403898672061847 0.8215273146316513
0.3472942103110106 -0.20481691511991018
0.24499559524388226 0.448974643451862
0.3729507557466516 -0.3249490874731633
0.24295234011755817 -0.5023665958909458
-0.06166664549465439 -6.716707884624196E-4
-0.4983225330150596 0.9324470693471052
-0.8264444128557209 -0.33545994187956296
-0.44882664048707843 -0.7669600648370445
0.6777665122249743 0.021318539182575647
-0.5424778591927784 0.7108596920632129
0.8850114134360809 0.6626573250439787
0.07107629938706106 0.5508307680777162
-0.8454247819065857 -0.10397848065683823
0.1549919273470115 0.4029877771336481
-0.33811930052751493 0.631769683220162
-0.2057839505389225 0.821704222573256
-0.239160379298744 -0.36904650444834486
-0.9131158063168903 0.7664893031144653
0.9162662900098093 -0.0933278021155044
0.6417297995128626 0.5611653222949906
0.04407535236799509 0.8089149767051032
0.4969412669221511 -0.5514292010159942
0.5947669272223122 -0.0938844107123884
0.6070686884483156 0.43552934537283483
-0.11183750436195417 -0.6108929760470123
-0.39702937428947505 0.2261948476550968
-0.060731930150897506 0.26519544996028954
-0.07795999682668131 0.388295823464444
-0.33998668527599696 0.20080810227155554
0.1574533345799396 0.6522726191548678
0.2017216721128514 -0.6514959419577582
0.33008162133498375 -0.4574056248672276
-0.8904858638391302 0.9147058498002165
-0.7921160155868996 0.9871747955091459
-0.3477906344689803 0.36370941771047205
-0.5332908113511645 0.7170433085267274
0.3981703097558229 -0.9945044655353068
-0.19614781874624598 -0.8047153023209661
-0.9737757105808107 -0.007506682408276122
-0.2994106171420645 0.5115028958566794
-0.8427294981524756 -0.6146291794004821
0.72013964325168 -0.37579075309128096
-0.698752840577054 0.5905448945440386
0.5797102116119868 0.9758462669793431
0.9392797378675879 0.9915497738831562
0.024873973576347463 0.7596518499865406
-0.6256674455509295 0.5805721784373421
0.2556339913145633 -0.1309894687847286
0.8265602622953256 -0.34800694441234503
0.5190454370836037 0.16184443682290883
0.8315630627937673 0.6720594364013495
-0.0751655482239344 -0.5527676170206512
-0.7005904063595165 0.03198807659501557
-0.2915425255523829 0.33982443088654923
0.5568681327950071 -0.011235498629049934
0.429634757607986 0.5895126208408108
-0.2592037011087478 -0.6197120023061877
-0.9585501114623589 -0.09226573377213931
-0.5781537712420572 0.06971470921469503
-0.29771993114842643 -0.1250057092324357
0.1680648634381583 0.14701022972536992
0.6554963357014205 -0.1072887085259484
0.729868967286984 0.03172681321085857
-0.2858084562414933 -0.028919702392020685
-0.06772939464813477 -0.6634857464984467
0.8230456781502744 -0.4731734521369344
-0.5431133729133497 0.9412412112195769
0.008467416234088754 0.3727571222289827
-0.7863027254808015 -0.3130045899576044
-0.3282589782669918 -0.7440786507566213
0.6379953993355594 -0.3594734572137721
-0.2527906934932804 0.15273104970879148
-0.8324996099379061 -0.5654549319878508
0.5764165086757398 -0.9639182491234832
0.4929663069638015 -0.09192307762043028
-0.5037301905979517 0.9386248877965955
-0.46369069165863297 -0.4770547987919944
-0.11996258446116315 -0.7361190067076921
-0.9344217494851119 -0.09471164296989087
-0.3014681415088185 0.8276229582212655
0.44701253504145266 -0.33852027778302496
0.29801450815384145 -0.1005889472647028
0.27073577457581766 -0.6287317116178057
0.9528465421513681 0.38059372283307336
-0.05315911169099352 -0.38843952134138315
-0.5049101484754774 0.4915150605906271
0.29999560756966637 -0.025103706891874022
-0.18072867337964427 0.20685879828759357
0.6092539910493573 -0.5010172252139766
0.896255890014275 -0.097477906248157
0.3302634841419927 -0.3819795956069443
0.9122663327442746 -0.04258088479667799
-0.7469743006482039 0.8021393122879841
0.8029363566895993 -0.4448212606925972
0.412066641003652 0.3059390025301698
Hidden Weights:
-0.5316842744058916 -0.04246202605576044
0.33292229792353756 -0.012641040519610902
Options: -E 0.5 -M 0.5
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 100
-E 0.5
-S 113129835
-H 2
-M 0.5
Input Weights:
0.4088222632788374 0.5012578226466649
-0.6625624070969929 0.629252123304938
0.8954233723949854 0.46843741500490266
-0.4151057697338172 0.6951933675740394
-0.5522245020700418 -0.1640491654930072
0.17076623241980915 -0.6980556270081983
0.3120369393547453 0.6283743790724161
-0.745458808868666 -0.3240482107905984
-0.6403898672061847 0.8215273146316513
0.3472942103110106 -0.20481691511991018
0.24499559524388226 0.448974643451862
0.3729507557466516 -0.3249490874731633
0.24295234011755817 -0.5023665958909458
-0.06166664549465439 -6.716707884624196E-4
-0.4983225330150596 0.9324470693471052
-0.8264444128557209 -0.33545994187956296
-0.44882664048707843 -0.7669600648370445
0.6777665122249743 0.021318539182575647
-0.5424778591927784 0.7108596920632129
0.8850114134360809 0.6626573250439787
0.07107629938706106 0.5508307680777162
-0.8454247819065857 -0.10397848065683823
0.1549919273470115 0.4029877771336481
-0.33811930052751493 0.631769683220162
-0.2057839505389225 0.821704222573256
-0.239160379298744 -0.36904650444834486
-0.9131158063168903 0.7664893031144653
0.9162662900098093 -0.0933278021155044
0.6417297995128626 0.5611653222949906
0.04407535236799509 0.8089149767051032
0.4969412669221511 -0.5514292010159942
0.5947669272223122 -0.0938844107123884
0.6070686884483156 0.43552934537283483
-0.11183750436195417 -0.6108929760470123
-0.39702937428947505 0.2261948476550968
-0.060731930150897506 0.26519544996028954
-0.07795999682668131 0.388295823464444
-0.33998668527599696 0.20080810227155554
0.1574533345799396 0.6522726191548678
0.2017216721128514 -0.6514959419577582
0.33008162133498375 -0.4574056248672276
-0.8904858638391302 0.9147058498002165
-0.7921160155868996 0.9871747955091459
-0.3477906344689803 0.36370941771047205
-0.5332908113511645 0.7170433085267274
0.3981703097558229 -0.9945044655353068
-0.19614781874624598 -0.8047153023209661
-0.9737757105808107 -0.007506682408276122
-0.2994106171420645 0.5115028958566794
-0.8427294981524756 -0.6146291794004821
0.72013964325168 -0.37579075309128096
-0.698752840577054 0.5905448945440386
0.5797102116119868 0.9758462669793431
0.9392797378675879 0.9915497738831562
0.024873973576347463 0.7596518499865406
-0.6256674455509295 0.5805721784373421
0.2556339913145633 -0.1309894687847286
0.8265602622953256 -0.34800694441234503
0.5190454370836037 0.16184443682290883
0.8315630627937673 0.6720594364013495
-0.0751655482239344 -0.5527676170206512
-0.7005904063595165 0.03198807659501557
-0.2915425255523829 0.33982443088654923
0.5568681327950071 -0.011235498629049934
0.429634757607986 0.5895126208408108
-0.2592037011087478 -0.6197120023061877
-0.9585501114623589 -0.09226573377213931
-0.5781537712420572 0.06971470921469503
-0.29771993114842643 -0.1250057092324357
0.1680648634381583 0.14701022972536992
0.6554963357014205 -0.1072887085259484
0.729868967286984 0.03172681321085857
-0.2858084562414933 -0.028919702392020685
-0.06772939464813477 -0.6634857464984467
0.8230456781502744 -0.4731734521369344
-0.5431133729133497 0.9412412112195769
0.008467416234088754 0.3727571222289827
-0.7863027254808015 -0.3130045899576044
-0.3282589782669918 -0.7440786507566213
0.6379953993355594 -0.3594734572137721
-0.2527906934932804 0.15273104970879148
-0.8324996099379061 -0.5654549319878508
0.5764165086757398 -0.9639182491234832
0.4929663069638015 -0.09192307762043028
-0.5037301905979517 0.9386248877965955
-0.46369069165863297 -0.4770547987919944
-0.11996258446116315 -0.7361190067076921
-0.9344217494851119 -0.09471164296989087
-0.3014681415088185 0.8276229582212655
0.44701253504145266 -0.33852027778302496
0.29801450815384145 -0.1005889472647028
0.27073577457581766 -0.6287317116178057
0.9528465421513681 0.38059372283307336
-0.05315911169099352 -0.38843952134138315
-0.5049101484754774 0.4915150605906271
0.29999560756966637 -0.025103706891874022
-0.18072867337964427 0.20685879828759357
0.6092539910493573 -0.5010172252139766
0.896255890014275 -0.097477906248157
0.3302634841419927 -0.3819795956069443
0.9122663327442746 -0.04258088479667799
-0.7469743006482039 0.8021393122879841
0.8029363566895993 -0.4448212606925972
0.412066641003652 0.3059390025301698
Hidden Weights:
-0.5122917247430705 0.06991346145880342
0.33292229792353756 -0.012641040519610902
=== Error on training data ===
Correctly Classified Instances 24720 75.919 %
Incorrectly Classified Instances 7841 24.081 %
Mean absolute error 0.3832
Root mean squared error 0.4289
Relative absolute error 104.8032 %
Root relative squared error 100.3137 %
Total Number of Instances 32561
=== Confusion Matrix ===
a b <-- classified as
0 7841 | a = >50K
0 24720 | b = <=50K
=== Error on test data ===
Correctly Classified Instances 12435 76.3774 %
Incorrectly Classified Instances 3846 23.6226 %
Mean absolute error 0.3811
Root mean squared error 0.4265
Relative absolute error 104.9201 %
Root relative squared error 100.4036 %
Total Number of Instances 16281
=== Confusion Matrix ===
a b <-- classified as
0 3846 | a = >50K
0 12435 | b = <=50K
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