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Calling LoadDataSet
LoadDataSet function took 37561.433 ms
10
MRMR
MLP logistic sgd
Time it took to train:
0.0565638542175
Accuracy scores:
0.772727272727
AdaBoostClassifier
Time it took to train:
0.0662350654602
Accuracy scores:
0.977272727273
DT classifier
Time it took to train:
0.000252962112427
Accuracy scores:
0.931818181818
Extra tree classifier
Time it took to train:
0.289350986481
Accuracy scores:
0.965909090909
Random Forest
Time it took to train:
0.0163359642029
Accuracy scores:
0.977272727273
SVM SVC
Time it took to train:
0.000377178192139
Accuracy scores:
0.977272727273
50
MRMR
MLP logistic sgd
Time it took to train:
0.0314130783081
Accuracy scores:
0.681818181818
AdaBoostClassifier
Time it took to train:
0.0946428775787
Accuracy scores:
0.965909090909
DT classifier
Time it took to train:
0.000703096389771
Accuracy scores:
0.920454545455
Extra tree classifier
Time it took to train:
0.0154960155487
Accuracy scores:
0.965909090909
Random Forest
Time it took to train:
0.0170421600342
Accuracy scores:
0.977272727273
SVM SVC
Time it took to train:
0.000484943389893
Accuracy scores:
0.977272727273
100
MRMR
MLP logistic sgd
Time it took to train:
0.0381319522858
Accuracy scores:
0.670454545455
AdaBoostClassifier
Time it took to train:
0.101425886154
Accuracy scores:
0.954545454545
DT classifier
Time it took to train:
0.00140690803528
Accuracy scores:
0.954545454545
Extra tree classifier
Time it took to train:
0.0154569149017
Accuracy scores:
0.988636363636
Random Forest
Time it took to train:
0.0167710781097
Accuracy scores:
0.965909090909
SVM SVC
Time it took to train:
0.000656127929688
Accuracy scores:
0.977272727273
150
MRMR
MLP logistic sgd
Time it took to train:
0.0412938594818
Accuracy scores:
0.738636363636
AdaBoostClassifier
Time it took to train:
0.114479064941
Accuracy scores:
0.965909090909
DT classifier
Time it took to train:
0.00241708755493
Accuracy scores:
0.943181818182
Extra tree classifier
Time it took to train:
0.0155520439148
Accuracy scores:
0.965909090909
Random Forest
Time it took to train:
0.0166249275208
Accuracy scores:
0.954545454545
SVM SVC
Time it took to train:
0.000838041305542
Accuracy scores:
0.977272727273
200
MRMR
MLP logistic sgd
Time it took to train:
0.188117027283
Accuracy scores:
0.806818181818
AdaBoostClassifier
Time it took to train:
0.117877006531
Accuracy scores:
0.965909090909
DT classifier
Time it took to train:
0.00231909751892
Accuracy scores:
0.920454545455
Extra tree classifier
Time it took to train:
0.0156779289246
Accuracy scores:
0.977272727273
Random Forest
Time it took to train:
0.016902923584
Accuracy scores:
0.965909090909
SVM SVC
Time it took to train:
0.00102519989014
Accuracy scores:
0.977272727273
250
MRMR
MLP logistic sgd
Time it took to train:
0.00728988647461
Accuracy scores:
0.534090909091
AdaBoostClassifier
Time it took to train:
0.128424882889
Accuracy scores:
0.965909090909
DT classifier
Time it took to train:
0.00286293029785
Accuracy scores:
0.920454545455
Extra tree classifier
Time it took to train:
0.0155990123749
Accuracy scores:
1.0
Random Forest
Time it took to train:
0.0168509483337
Accuracy scores:
0.965909090909
SVM SVC
Time it took to train:
0.00118899345398
Accuracy scores:
0.977272727273
10
JMI
MLP logistic sgd
Time it took to train:
0.0726721286774
Accuracy scores:
0.829545454545
AdaBoostClassifier
Time it took to train:
0.061224937439
Accuracy scores:
0.965909090909
DT classifier
Time it took to train:
0.00022292137146
Accuracy scores:
0.988636363636
Extra tree classifier
Time it took to train:
0.0152850151062
Accuracy scores:
0.988636363636
Random Forest
Time it took to train:
0.0160400867462
Accuracy scores:
0.965909090909
SVM SVC
Time it took to train:
0.000354051589966
Accuracy scores:
0.977272727273
50
JMI
MLP logistic sgd
Time it took to train:
0.106266021729
Accuracy scores:
0.875
AdaBoostClassifier
Time it took to train:
0.0928840637207
Accuracy scores:
0.965909090909
DT classifier
Time it took to train:
0.000722885131836
Accuracy scores:
0.920454545455
Extra tree classifier
Time it took to train:
0.0154759883881
Accuracy scores:
0.988636363636
Random Forest
Time it took to train:
0.0162570476532
Accuracy scores:
0.977272727273
SVM SVC
Time it took to train:
0.000479936599731
Accuracy scores:
0.977272727273
100
JMI
MLP logistic sgd
Time it took to train:
0.129193067551
Accuracy scores:
0.931818181818
AdaBoostClassifier
Time it took to train:
0.100891113281
Accuracy scores:
0.965909090909
DT classifier
Time it took to train:
0.00107002258301
Accuracy scores:
0.943181818182
Extra tree classifier
Time it took to train:
0.0157351493835
Accuracy scores:
0.977272727273
Random Forest
Time it took to train:
0.0165548324585
Accuracy scores:
0.977272727273
SVM SVC
Time it took to train:
0.000653028488159
Accuracy scores:
0.977272727273
150
JMI
MLP logistic sgd
Time it took to train:
0.0519788265228
Accuracy scores:
0.727272727273
AdaBoostClassifier
Time it took to train:
0.110514879227
Accuracy scores:
0.965909090909
DT classifier
Time it took to train:
0.00152897834778
Accuracy scores:
0.931818181818
Extra tree classifier
Time it took to train:
0.015438079834
Accuracy scores:
1.0
Random Forest
Time it took to train:
0.0165548324585
Accuracy scores:
1.0
SVM SVC
Time it took to train:
0.000844955444336
Accuracy scores:
0.977272727273
200
JMI
MLP logistic sgd
Time it took to train:
0.0409348011017
Accuracy scores:
0.795454545455
AdaBoostClassifier
Time it took to train:
0.118056774139
Accuracy scores:
0.977272727273
DT classifier
Time it took to train:
0.00198292732239
Accuracy scores:
0.931818181818
Extra tree classifier
Time it took to train:
0.0155279636383
Accuracy scores:
1.0
Random Forest
Time it took to train:
0.0170230865479
Accuracy scores:
0.965909090909
SVM SVC
Time it took to train:
0.00102019309998
Accuracy scores:
0.977272727273
250
JMI
MLP logistic sgd
Time it took to train:
0.0803778171539
Accuracy scores:
0.727272727273
AdaBoostClassifier
Time it took to train:
0.125571966171
Accuracy scores:
0.977272727273
DT classifier
Time it took to train:
0.00243282318115
Accuracy scores:
0.931818181818
Extra tree classifier
Time it took to train:
0.015506029129
Accuracy scores:
1.0
Random Forest
Time it took to train:
0.017315864563
Accuracy scores:
0.977272727273
SVM SVC
Time it took to train:
0.00119495391846
Accuracy scores:
0.977272727273
10
JMIM
MLP logistic sgd
Time it took to train:
0.0134871006012
Accuracy scores:
0.681818181818
AdaBoostClassifier
Time it took to train:
0.0610609054565
Accuracy scores:
0.965909090909
DT classifier
Time it took to train:
0.000233888626099
Accuracy scores:
0.977272727273
Extra tree classifier
Time it took to train:
0.0153849124908
Accuracy scores:
0.965909090909
Random Forest
Time it took to train:
0.0160031318665
Accuracy scores:
0.943181818182
SVM SVC
Time it took to train:
0.000349998474121
Accuracy scores:
0.977272727273
50
JMIM
MLP logistic sgd
Time it took to train:
0.00376510620117
Accuracy scores:
0.681818181818
AdaBoostClassifier
Time it took to train:
0.0954618453979
Accuracy scores:
0.988636363636
DT classifier
Time it took to train:
0.000595092773438
Accuracy scores:
0.965909090909
Extra tree classifier
Time it took to train:
0.015487909317
Accuracy scores:
0.988636363636
Random Forest
Time it took to train:
0.0163300037384
Accuracy scores:
0.931818181818
SVM SVC
Time it took to train:
0.000483989715576
Accuracy scores:
0.977272727273
100
JMIM
MLP logistic sgd
Time it took to train:
0.0125181674957
Accuracy scores:
0.681818181818
AdaBoostClassifier
Time it took to train:
0.10328412056
Accuracy scores:
0.954545454545
DT classifier
Time it took to train:
0.00102186203003
Accuracy scores:
0.965909090909
Extra tree classifier
Time it took to train:
0.0155799388885
Accuracy scores:
0.954545454545
Random Forest
Time it took to train:
0.0164430141449
Accuracy scores:
0.954545454545
SVM SVC
Time it took to train:
0.000654935836792
Accuracy scores:
0.977272727273
150
JMIM
MLP logistic sgd
Time it took to train:
0.0163850784302
Accuracy scores:
0.681818181818
AdaBoostClassifier
Time it took to train:
0.11154294014
Accuracy scores:
0.965909090909
DT classifier
Time it took to train:
0.00130391120911
Accuracy scores:
0.931818181818
Extra tree classifier
Time it took to train:
0.0155119895935
Accuracy scores:
0.988636363636
Random Forest
Time it took to train:
0.0165820121765
Accuracy scores:
0.965909090909
SVM SVC
Time it took to train:
0.000839948654175
Accuracy scores:
0.977272727273
200
JMIM
MLP logistic sgd
Time it took to train:
0.0048508644104
Accuracy scores:
0.681818181818
AdaBoostClassifier
Time it took to train:
0.120047092438
Accuracy scores:
0.965909090909
DT classifier
Time it took to train:
0.00167393684387
Accuracy scores:
0.931818181818
Extra tree classifier
Time it took to train:
0.0155959129333
Accuracy scores:
0.977272727273
Random Forest
Time it took to train:
0.0167489051819
Accuracy scores:
0.988636363636
SVM SVC
Time it took to train:
0.00101113319397
Accuracy scores:
0.977272727273
250
JMIM
MLP logistic sgd
Time it took to train:
0.0147478580475
Accuracy scores:
0.681818181818
AdaBoostClassifier
Time it took to train:
0.128279924393
Accuracy scores:
0.965909090909
DT classifier
Time it took to train:
0.00206589698792
Accuracy scores:
0.943181818182
Extra tree classifier
Time it took to train:
0.0157248973846
Accuracy scores:
0.943181818182
Random Forest
Time it took to train:
0.0168440341949
Accuracy scores:
0.988636363636
SVM SVC
Time it took to train:
0.00119519233704
Accuracy scores:
0.977272727273