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digits-rf-0.log
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digits-rf-0.log
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Data set: digits
Algorithm: rf
Loading digits data set...
Creating random forest hyper classifier...
Running trial 0...
Creating trial data...
Applying classifier to trial...
No cached result "runs/digits/0/rf/estimators(500)-split(0.5).pickle", building and running classifier...
64
8.0
0.5
4
run: estimators(500)-split(0.5)
parameters: {'n_estimators': 500, 'split': 0.5}
ml ce: 0.0200333889816
ml rmse: 0.585010309114
sk acc: 0.979966611018
sk f1: 0.979757050889
sk prec: 0.980158580573
sk recl: 0.979966611018
label: 0
ml auc: 0.991666666667
sk auc: 0.991666666667
label: 1
ml auc: 0.997217068646
sk auc: 0.997217068646
label: 2
ml auc: 1.0
sk auc: 1.0
label: 3
ml auc: 1.0
sk auc: 1.0
label: 4
ml auc: 0.989015174599
sk auc: 0.989015174599
label: 5
ml auc: 0.990739022882
sk auc: 0.990739022882
label: 6
ml auc: 0.991803278689
sk auc: 0.991803278689
label: 7
ml auc: 0.998148148148
sk auc: 0.998148148148
label: 8
ml auc: 0.937806743578
sk auc: 0.937806743578
label: 9
ml auc: 0.990739022882
sk auc: 0.990739022882
Saving result "runs/digits/0/rf/estimators(500)-split(0.5).pickle"...
No cached result "runs/digits/0/rf/estimators(500)-split(1).pickle", building and running classifier...
64
8.0
1
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run: estimators(500)-split(1)
parameters: {'n_estimators': 500, 'split': 1}
ml ce: 0.0183639398998
ml rmse: 0.663878420794
sk acc: 0.9816360601
sk f1: 0.981618634202
sk prec: 0.982171314813
sk recl: 0.9816360601
label: 0
ml auc: 0.991666666667
sk auc: 0.991666666667
label: 1
ml auc: 0.996289424861
sk auc: 0.996289424861
label: 2
ml auc: 1.0
sk auc: 1.0
label: 3
ml auc: 0.991803278689
sk auc: 0.991803278689
label: 4
ml auc: 0.989015174599
sk auc: 0.989015174599
label: 5
ml auc: 0.991666666667
sk auc: 0.991666666667
label: 6
ml auc: 0.991803278689
sk auc: 0.991803278689
label: 7
ml auc: 0.999074074074
sk auc: 0.999074074074
label: 8
ml auc: 0.955972337306
sk auc: 0.955972337306
label: 9
ml auc: 0.989811379097
sk auc: 0.989811379097
Saving result "runs/digits/0/rf/estimators(500)-split(1).pickle"...
No cached result "runs/digits/0/rf/estimators(500)-split(2).pickle", building and running classifier...
64
8.0
2
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run: estimators(500)-split(2)
parameters: {'n_estimators': 500, 'split': 2}
ml ce: 0.025041736227
ml rmse: 0.700584063514
sk acc: 0.974958263773
sk f1: 0.974862318851
sk prec: 0.975783932474
sk recl: 0.974958263773
label: 0
ml auc: 0.990739022882
sk auc: 0.990739022882
label: 1
ml auc: 0.995361781076
sk auc: 0.995361781076
label: 2
ml auc: 0.991525423729
sk auc: 0.991525423729
label: 3
ml auc: 0.991803278689
sk auc: 0.991803278689
label: 4
ml auc: 0.979889085258
sk auc: 0.979889085258
label: 5
ml auc: 0.991666666667
sk auc: 0.991666666667
label: 6
ml auc: 0.991803278689
sk auc: 0.991803278689
label: 7
ml auc: 0.998148148148
sk auc: 0.998148148148
label: 8
ml auc: 0.938730957996
sk auc: 0.938730957996
label: 9
ml auc: 0.989811379097
sk auc: 0.989811379097
Saving result "runs/digits/0/rf/estimators(500)-split(2).pickle"...
No cached result "runs/digits/0/rf/estimators(500)-split(4).pickle", building and running classifier...
64
8.0
4
32
run: estimators(500)-split(4)
parameters: {'n_estimators': 500, 'split': 4}
ml ce: 0.0434056761269
ml rmse: 0.876325611648
sk acc: 0.956594323873
sk f1: 0.956255312507
sk prec: 0.957300317632
sk recl: 0.956594323873
label: 0
ml auc: 0.981478045764
sk auc: 0.981478045764
label: 1
ml auc: 0.995361781076
sk auc: 0.995361781076
label: 2
ml auc: 0.989673571877
sk auc: 0.989673571877
label: 3
ml auc: 0.974480468036
sk auc: 0.974480468036
label: 4
ml auc: 0.978030349199
sk auc: 0.978030349199
label: 5
ml auc: 0.966666666667
sk auc: 0.966666666667
label: 6
ml auc: 0.991803278689
sk auc: 0.991803278689
label: 7
ml auc: 0.998148148148
sk auc: 0.998148148148
label: 8
ml auc: 0.910096245777
sk auc: 0.910096245777
label: 9
ml auc: 0.971289424861
sk auc: 0.971289424861
Saving result "runs/digits/0/rf/estimators(500)-split(4).pickle"...
No cached result "runs/digits/0/rf/estimators(500)-split(8).pickle", building and running classifier...
64
8.0
8
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run: estimators(500)-split(8)
parameters: {'n_estimators': 500, 'split': 8}
ml ce: 0.0651085141903
ml rmse: 1.11747389821
sk acc: 0.93489148581
sk f1: 0.933756794
sk prec: 0.935625212245
sk recl: 0.93489148581
label: 0
ml auc: 0.97314471243
sk auc: 0.97314471243
label: 1
ml auc: 0.985173160173
sk auc: 0.985173160173
label: 2
ml auc: 0.981198995606
sk auc: 0.981198995606
label: 3
ml auc: 0.970762995917
sk auc: 0.970762995917
label: 4
ml auc: 0.978030349199
sk auc: 0.978030349199
label: 5
ml auc: 0.957405689549
sk auc: 0.957405689549
label: 6
ml auc: 0.983606557377
sk auc: 0.983606557377
label: 7
ml auc: 0.985969868173
sk auc: 0.985969868173
label: 8
ml auc: 0.857447893429
sk auc: 0.857447893429
label: 9
ml auc: 0.962028447743
sk auc: 0.962028447743
Saving result "runs/digits/0/rf/estimators(500)-split(8).pickle"...
Clearing trial data from memory...
Running trial 1...
Creating trial data...
Applying classifier to trial...
No cached result "runs/digits/1/rf/estimators(500)-split(0.5).pickle", building and running classifier...
64
8.0
0.5
4
run: estimators(500)-split(0.5)
parameters: {'n_estimators': 500, 'split': 0.5}
ml ce: 0.0317195325543
ml rmse: 0.838354378195
sk acc: 0.968280467446
sk f1: 0.96829697282
sk prec: 0.968642660695
sk recl: 0.968280467446
label: 0
ml auc: 0.991525423729
sk auc: 0.991525423729
label: 1
ml auc: 0.989015174599
sk auc: 0.989015174599
label: 2
ml auc: 0.999074074074
sk auc: 0.999074074074
label: 3
ml auc: 0.981747821318
sk auc: 0.981747821318
label: 4
ml auc: 0.974072356215
sk auc: 0.974072356215
label: 5
ml auc: 0.972621731976
sk auc: 0.972621731976
label: 6
ml auc: 0.990739022882
sk auc: 0.990739022882
label: 7
ml auc: 0.989811379097
sk auc: 0.989811379097
label: 8
ml auc: 0.964593026962
sk auc: 0.964593026962
label: 9
ml auc: 0.970361781076
sk auc: 0.970361781076
Saving result "runs/digits/1/rf/estimators(500)-split(0.5).pickle"...
No cached result "runs/digits/1/rf/estimators(500)-split(1).pickle", building and running classifier...
64
8.0
1
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run: estimators(500)-split(1)
parameters: {'n_estimators': 500, 'split': 1}
ml ce: 0.0317195325543
ml rmse: 0.801709359116
sk acc: 0.968280467446
sk f1: 0.968262748153
sk prec: 0.969284828751
sk recl: 0.968280467446
label: 0
ml auc: 0.991525423729
sk auc: 0.991525423729
label: 1
ml auc: 0.998141263941
sk auc: 0.998141263941
label: 2
ml auc: 0.999074074074
sk auc: 0.999074074074
label: 3
ml auc: 0.966283746724
sk auc: 0.966283746724
label: 4
ml auc: 0.974072356215
sk auc: 0.974072356215
label: 5
ml auc: 0.965354378695
sk auc: 0.965354378695
label: 6
ml auc: 0.999072356215
sk auc: 0.999072356215
label: 7
ml auc: 0.988883735312
sk auc: 0.988883735312
label: 8
ml auc: 0.955972337306
sk auc: 0.955972337306
label: 9
ml auc: 0.985173160173
sk auc: 0.985173160173
Saving result "runs/digits/1/rf/estimators(500)-split(1).pickle"...
No cached result "runs/digits/1/rf/estimators(500)-split(2).pickle", building and running classifier...
64
8.0
2
16
run: estimators(500)-split(2)
parameters: {'n_estimators': 500, 'split': 2}
ml ce: 0.0300500834725
ml rmse: 0.739986012592
sk acc: 0.969949916528
sk f1: 0.970048963091
sk prec: 0.971028675517
sk recl: 0.969949916528
label: 0
ml auc: 0.991525423729
sk auc: 0.991525423729
label: 1
ml auc: 0.989944542629
sk auc: 0.989944542629
label: 2
ml auc: 1.0
sk auc: 1.0
label: 3
ml auc: 0.973551100006
sk auc: 0.973551100006
label: 4
ml auc: 0.974072356215
sk auc: 0.974072356215
label: 5
ml auc: 0.965354378695
sk auc: 0.965354378695
label: 6
ml auc: 0.999072356215
sk auc: 0.999072356215
label: 7
ml auc: 0.988883735312
sk auc: 0.988883735312
label: 8
ml auc: 0.965517241379
sk auc: 0.965517241379
label: 9
ml auc: 0.985173160173
sk auc: 0.985173160173
Saving result "runs/digits/1/rf/estimators(500)-split(2).pickle"...
No cached result "runs/digits/1/rf/estimators(500)-split(4).pickle", building and running classifier...
64
8.0
4
32
run: estimators(500)-split(4)
parameters: {'n_estimators': 500, 'split': 4}
ml ce: 0.0434056761269
ml rmse: 0.863854003617
sk acc: 0.956594323873
sk f1: 0.956503686414
sk prec: 0.957215863269
sk recl: 0.956594323873
label: 0
ml auc: 0.991525423729
sk auc: 0.991525423729
label: 1
ml auc: 0.989944542629
sk auc: 0.989944542629
label: 2
ml auc: 0.999074074074
sk auc: 0.999074074074
label: 3
ml auc: 0.970762995917
sk auc: 0.970762995917
label: 4
ml auc: 0.982405689549
sk auc: 0.982405689549
label: 5
ml auc: 0.964425010665
sk auc: 0.964425010665
label: 6
ml auc: 0.990739022882
sk auc: 0.990739022882
label: 7
ml auc: 0.979622758194
sk auc: 0.979622758194
label: 8
ml auc: 0.929186053923
sk auc: 0.929186053923
label: 9
ml auc: 0.960173160173
sk auc: 0.960173160173
Saving result "runs/digits/1/rf/estimators(500)-split(4).pickle"...
No cached result "runs/digits/1/rf/estimators(500)-split(8).pickle", building and running classifier...
64
8.0
8
64
run: estimators(500)-split(8)
parameters: {'n_estimators': 500, 'split': 8}
ml ce: 0.0450751252087
ml rmse: 0.928135618436
sk acc: 0.954924874791
sk f1: 0.954660921999
sk prec: 0.955332215464
sk recl: 0.954924874791
label: 0
ml auc: 0.991525423729
sk auc: 0.991525423729
label: 1
ml auc: 0.989015174599
sk auc: 0.989015174599
label: 2
ml auc: 0.997222222222
sk auc: 0.997222222222
label: 3
ml auc: 0.961636906576
sk auc: 0.961636906576
label: 4
ml auc: 0.990739022882
sk auc: 0.990739022882
label: 5
ml auc: 0.966283746724
sk auc: 0.966283746724
label: 6
ml auc: 0.990739022882
sk auc: 0.990739022882
label: 7
ml auc: 0.979622758194
sk auc: 0.979622758194
label: 8
ml auc: 0.91964114985
sk auc: 0.91964114985
label: 9
ml auc: 0.962028447743
sk auc: 0.962028447743
Saving result "runs/digits/1/rf/estimators(500)-split(8).pickle"...
Clearing trial data from memory...
Running trial 2...
Creating trial data...
Applying classifier to trial...
No cached result "runs/digits/2/rf/estimators(500)-split(0.5).pickle", building and running classifier...
64
8.0
0.5
4
run: estimators(500)-split(0.5)
parameters: {'n_estimators': 500, 'split': 0.5}
ml ce: 0.0183639398998
ml rmse: 0.589275325306
sk acc: 0.9816360601
sk f1: 0.981554266447
sk prec: 0.982164069853
sk recl: 0.9816360601
label: 0
ml auc: 0.999074074074
sk auc: 0.999074074074
label: 1
ml auc: 0.99907063197
sk auc: 0.99907063197
label: 2
ml auc: 1.0
sk auc: 1.0
label: 3
ml auc: 0.981747821318
sk auc: 0.981747821318
label: 4
ml auc: 0.991666666667
sk auc: 0.991666666667
label: 5
ml auc: 0.997211895911
sk auc: 0.997211895911
label: 6
ml auc: 0.983333333333
sk auc: 0.983333333333
label: 7
ml auc: 0.997217068646
sk auc: 0.997217068646
label: 8
ml auc: 0.990455095927
sk auc: 0.990455095927
label: 9
ml auc: 0.958333333333
sk auc: 0.958333333333
Saving result "runs/digits/2/rf/estimators(500)-split(0.5).pickle"...
No cached result "runs/digits/2/rf/estimators(500)-split(1).pickle", building and running classifier...
64
8.0
1
8
run: estimators(500)-split(1)
parameters: {'n_estimators': 500, 'split': 1}
ml ce: 0.0233722871452
ml rmse: 0.705333840374
sk acc: 0.976627712855
sk f1: 0.976548028232
sk prec: 0.977064346034
sk recl: 0.976627712855
label: 0
ml auc: 0.999074074074
sk auc: 0.999074074074
label: 1
ml auc: 0.989944542629
sk auc: 0.989944542629
label: 2
ml auc: 0.991525423729
sk auc: 0.991525423729
label: 3
ml auc: 0.973551100006
sk auc: 0.973551100006
label: 4
ml auc: 0.991666666667
sk auc: 0.991666666667
label: 5
ml auc: 0.997211895911
sk auc: 0.997211895911
label: 6
ml auc: 0.983333333333
sk auc: 0.983333333333
label: 7
ml auc: 0.997217068646
sk auc: 0.997217068646
label: 8
ml auc: 0.989530881509
sk auc: 0.989530881509
label: 9
ml auc: 0.957405689549
sk auc: 0.957405689549
Saving result "runs/digits/2/rf/estimators(500)-split(1).pickle"...
No cached result "runs/digits/2/rf/estimators(500)-split(2).pickle", building and running classifier...
64
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run: estimators(500)-split(2)
parameters: {'n_estimators': 500, 'split': 2}
ml ce: 0.0233722871452
ml rmse: 0.662619882372
sk acc: 0.976627712855
sk f1: 0.976577517502
sk prec: 0.977149370147
sk recl: 0.976627712855
label: 0
ml auc: 0.999074074074
sk auc: 0.999074074074
label: 1
ml auc: 0.983606557377
sk auc: 0.983606557377
label: 2
ml auc: 0.983050847458
sk auc: 0.983050847458
label: 3
ml auc: 0.980818453288
sk auc: 0.980818453288
label: 4
ml auc: 0.991666666667
sk auc: 0.991666666667
label: 5
ml auc: 0.997211895911
sk auc: 0.997211895911
label: 6
ml auc: 0.983333333333
sk auc: 0.983333333333
label: 7
ml auc: 0.99814471243
sk auc: 0.99814471243
label: 8
ml auc: 0.997227356747
sk auc: 0.997227356747
label: 9
ml auc: 0.956478045764
sk auc: 0.956478045764
Saving result "runs/digits/2/rf/estimators(500)-split(2).pickle"...
No cached result "runs/digits/2/rf/estimators(500)-split(4).pickle", building and running classifier...
64
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run: estimators(500)-split(4)
parameters: {'n_estimators': 500, 'split': 4}
ml ce: 0.0317195325543
ml rmse: 0.867710513877
sk acc: 0.968280467446
sk f1: 0.968230057533
sk prec: 0.968823017075
sk recl: 0.968280467446
label: 0
ml auc: 0.998148148148
sk auc: 0.998148148148
label: 1
ml auc: 0.959016393443
sk auc: 0.959016393443
label: 2
ml auc: 0.981198995606
sk auc: 0.981198995606
label: 3
ml auc: 0.963495642635
sk auc: 0.963495642635
label: 4
ml auc: 0.999072356215
sk auc: 0.999072356215
label: 5
ml auc: 0.980818453288
sk auc: 0.980818453288
label: 6
ml auc: 0.975
sk auc: 0.975
label: 7
ml auc: 0.999072356215
sk auc: 0.999072356215
label: 8
ml auc: 0.999075785582
sk auc: 0.999075785582
label: 9
ml auc: 0.970361781076
sk auc: 0.970361781076
Saving result "runs/digits/2/rf/estimators(500)-split(4).pickle"...
No cached result "runs/digits/2/rf/estimators(500)-split(8).pickle", building and running classifier...
64
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run: estimators(500)-split(8)
parameters: {'n_estimators': 500, 'split': 8}
ml ce: 0.0634390651085
ml rmse: 1.11373276318
sk acc: 0.936560934891
sk f1: 0.936296978407
sk prec: 0.937920259607
sk recl: 0.936560934891
label: 0
ml auc: 0.988747645951
sk auc: 0.988747645951
label: 1
ml auc: 0.957157657383
sk auc: 0.957157657383
label: 2
ml auc: 0.971798493409
sk auc: 0.971798493409
label: 3
ml auc: 0.930708757389
sk auc: 0.930708757389
label: 4
ml auc: 0.959245516388
sk auc: 0.959245516388
label: 5
ml auc: 0.979889085258
sk auc: 0.979889085258
label: 6
ml auc: 0.941666666667
sk auc: 0.941666666667
label: 7
ml auc: 0.994434137291
sk auc: 0.994434137291
label: 8
ml auc: 0.988606667092
sk auc: 0.988606667092
label: 9
ml auc: 0.937028447743
sk auc: 0.937028447743
Saving result "runs/digits/2/rf/estimators(500)-split(8).pickle"...
Clearing trial data from memory...