MLcomp - Viewing Run 10794

Run 10794

Creator	chinamrwu
Program	liblinear-s6-B1
Dataset	pssmOfprotein
Task type	BinaryClassification
Created	2y203d ago
Download	Login required!

Status: Done!

Total Time	15m26s
Max Memory Usage	62M
Domain	MulticlassClassification
Learn time
Train error	0.151
Predict train time
Test error	0.424
Predict test time

Log file

... (lines omitted) ...
Objective value = 3.004895
#nonzeros/#features = 209/211
=== END _one-vs-all-learner1: ./run learn ../data1 --- OK [6s]

===== One versus all: training label y=2 versus the rest =====
=== START _one-vs-all-learner2: ./run learn ../data2
..*.*
optimization finished, #iter = 32
Objective value = 2.749896
#nonzeros/#features = 209/211
=== END _one-vs-all-learner2: ./run learn ../data2 --- OK [6s]

===== One versus all: training label y=3 versus the rest =====
=== START _one-vs-all-learner3: ./run learn ../data3
.............
optimization finished, #iter = 135
Objective value = 87.067443
#nonzeros/#features = 211/211
=== END _one-vs-all-learner3: ./run learn ../data3 --- OK [20s]

===== One versus all: training label y=4 versus the rest =====
=== START _one-vs-all-learner4: ./run learn ../data4
.............*.
optimization finished, #iter = 141
Objective value = 21.311471
#nonzeros/#features = 211/211
=== END _one-vs-all-learner4: ./run learn ../data4 --- OK [21s]

===== One versus all: training label y=5 versus the rest =====
=== START _one-vs-all-learner5: ./run learn ../data5
....**.**
optimization finished, #iter = 53
Objective value = 3.587810
#nonzeros/#features = 206/211
=== END _one-vs-all-learner5: ./run learn ../data5 --- OK [8s]

===== One versus all: training label y=6 versus the rest =====
=== START _one-vs-all-learner6: ./run learn ../data6
...**
optimization finished, #iter = 37
Objective value = 4.368429
#nonzeros/#features = 209/211
=== END _one-vs-all-learner6: ./run learn ../data6 --- OK [6s]

===== One versus all: training label y=7 versus the rest =====
=== START _one-vs-all-learner7: ./run learn ../data7
..........
optimization finished, #iter = 103
Objective value = 147.151388
#nonzeros/#features = 210/211
=== END _one-vs-all-learner7: ./run learn ../data7 --- OK [16s]

===== One versus all: training label y=8 versus the rest =====
=== START _one-vs-all-learner8: ./run learn ../data8
........*...**
optimization finished, #iter = 119
Objective value = 5.176246
#nonzeros/#features = 210/211
=== END _one-vs-all-learner8: ./run learn ../data8 --- OK [18s]

===== One versus all: training label y=9 versus the rest =====
=== START _one-vs-all-learner9: ./run learn ../data9
.........................*.*
optimization finished, #iter = 263
Objective value = 20.140145
#nonzeros/#features = 211/211
=== END _one-vs-all-learner9: ./run learn ../data9 --- OK [38s]

===== One versus all: training label y=10 versus the rest =====
=== START _one-vs-all-learner10: ./run learn ../data10
...................*..*
optimization finished, #iter = 219
Objective value = 13.399335
#nonzeros/#features = 211/211
=== END _one-vs-all-learner10: ./run learn ../data10 --- OK [32s]

===== One versus all: training label y=11 versus the rest =====
=== START _one-vs-all-learner11: ./run learn ../data11
..................*...
optimization finished, #iter = 218
Objective value = 40.664689
#nonzeros/#features = 211/211
=== END _one-vs-all-learner11: ./run learn ../data11 --- OK [32s]

===== One versus all: training label y=12 versus the rest =====
=== START _one-vs-all-learner12: ./run learn ../data12
.............................
optimization finished, #iter = 295
Objective value = 106.491609
#nonzeros/#features = 211/211
=== END _one-vs-all-learner12: ./run learn ../data12 --- OK [43s]

===== One versus all: training label y=13 versus the rest =====
=== START _one-vs-all-learner13: ./run learn ../data13
............*
optimization finished, #iter = 122
Objective value = 11.183748
#nonzeros/#features = 211/211
=== END _one-vs-all-learner13: ./run learn ../data13 --- OK [19s]

===== One versus all: training label y=14 versus the rest =====
=== START _one-vs-all-learner14: ./run learn ../data14
.......**..*
optimization finished, #iter = 91
Objective value = 8.898389
#nonzeros/#features = 208/211
=== END _one-vs-all-learner14: ./run learn ../data14 --- OK [13s]

===== One versus all: training label y=15 versus the rest =====
=== START _one-vs-all-learner15: ./run learn ../data15
...*
optimization finished, #iter = 37
Objective value = 3.626955
#nonzeros/#features = 208/211
=== END _one-vs-all-learner15: ./run learn ../data15 --- OK [5s]

===== One versus all: training label y=16 versus the rest =====
=== START _one-vs-all-learner16: ./run learn ../data16
.............................................*...
optimization finished, #iter = 486
Objective value = 36.996302
#nonzeros/#features = 211/211
=== END _one-vs-all-learner16: ./run learn ../data16 --- OK [70s]

===== One versus all: training label y=17 versus the rest =====
=== START _one-vs-all-learner17: ./run learn ../data17
..........*
optimization finished, #iter = 106
Objective value = 13.172233
#nonzeros/#features = 210/211
=== END _one-vs-all-learner17: ./run learn ../data17 --- OK [15s]

===== One versus all: training label y=18 versus the rest =====
=== START _one-vs-all-learner18: ./run learn ../data18
......................................................................
optimization finished, #iter = 700
Objective value = 62.153646
#nonzeros/#features = 211/211
=== END _one-vs-all-learner18: ./run learn ../data18 --- OK [101s]

===== One versus all: training label y=19 versus the rest =====
=== START _one-vs-all-learner19: ./run learn ../data19
...................................*..
optimization finished, #iter = 372
Objective value = 36.684645
#nonzeros/#features = 211/211
=== END _one-vs-all-learner19: ./run learn ../data19 --- OK [54s]

===== One versus all: training label y=20 versus the rest =====
=== START _one-vs-all-learner20: ./run learn ../data20
................................................*
optimization finished, #iter = 481
Objective value = 69.699602
#nonzeros/#features = 210/211
=== END _one-vs-all-learner20: ./run learn ../data20 --- OK [70s]

===== One versus all: training label y=21 versus the rest =====
=== START _one-vs-all-learner21: ./run learn ../data21
................
optimization finished, #iter = 169
Objective value = 51.106706
#nonzeros/#features = 211/211
=== END _one-vs-all-learner21: ./run learn ../data21 --- OK [25s]

===== One versus all: training label y=22 versus the rest =====
=== START _one-vs-all-learner22: ./run learn ../data22
....................................................................................................
optimization finished, #iter = 1000

WARNING: reaching max number of iterations
Objective value = 76.297690
#nonzeros/#features = 211/211
=== END _one-vs-all-learner22: ./run learn ../data22 --- OK [146s]

===== One versus all: training label y=23 versus the rest =====
=== START _one-vs-all-learner23: ./run learn ../data23
...............
optimization finished, #iter = 159
Objective value = 13.972935
#nonzeros/#features = 211/211
=== END _one-vs-all-learner23: ./run learn ../data23 --- OK [24s]

===== One versus all: training label y=24 versus the rest =====
=== START _one-vs-all-learner24: ./run learn ../data24
.**
optimization finished, #iter = 19
Objective value = 1.004856
#nonzeros/#features = 192/211
=== END _one-vs-all-learner24: ./run learn ../data24 --- OK [3s]

===== One versus all: training label y=25 versus the rest =====
=== START _one-vs-all-learner25: ./run learn ../data25
.....................*......*..
optimization finished, #iter = 297
Objective value = 60.044673
#nonzeros/#features = 210/211
=== END _one-vs-all-learner25: ./run learn ../data25 --- OK [44s]

===== One versus all: training label y=26 versus the rest =====
=== START _one-vs-all-learner26: ./run learn ../data26
...................................
optimization finished, #iter = 355
Objective value = 248.895574
#nonzeros/#features = 211/211
=== END _one-vs-all-learner26: ./run learn ../data26 --- OK [52s]

===== One versus all: training label y=27 versus the rest =====
=== START _one-vs-all-learner27: ./run learn ../data27
*
optimization finished, #iter = 7
Objective value = 0.899878
#nonzeros/#features = 195/211
=== END _one-vs-all-learner27: ./run learn ../data27 --- OK [2s]

=== END program1: ./run learn ../dataset3/train --- OK [897s]

===== MAIN: predict/evaluate on train data =====
=== START program4: ./run stripLabels ../dataset3/train ../program0/evalTrain.in
=== END program4: ./run stripLabels ../dataset3/train ../program0/evalTrain.in --- OK [0s]
=== START program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out
=== START _one-vs-all-learner1: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y1
Accuracy = 1.28342% (24/1870)
=== END _one-vs-all-learner1: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y1 --- OK [0s]
=== START _one-vs-all-learner2: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y2
Accuracy = 0.962567% (18/1870)
=== END _one-vs-all-learner2: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y2 --- OK [1s]
=== START _one-vs-all-learner3: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y3
Accuracy = 6.36364% (119/1870)
=== END _one-vs-all-learner3: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y3 --- OK [0s]
=== START _one-vs-all-learner4: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y4
Accuracy = 1.87166% (35/1870)
=== END _one-vs-all-learner4: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y4 --- OK [1s]
=== START _one-vs-all-learner5: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y5
Accuracy = 1.28342% (24/1870)
=== END _one-vs-all-learner5: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y5 --- OK [0s]
=== START _one-vs-all-learner6: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y6
Accuracy = 1.76471% (33/1870)
=== END _one-vs-all-learner6: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y6 --- OK [1s]
=== START _one-vs-all-learner7: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y7
Accuracy = 11.3904% (213/1870)
=== END _one-vs-all-learner7: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y7 --- OK [0s]
=== START _one-vs-all-learner8: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y8
Accuracy = 1.44385% (27/1870)
=== END _one-vs-all-learner8: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y8 --- OK [1s]
=== START _one-vs-all-learner9: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y9
Accuracy = 1.97861% (37/1870)
=== END _one-vs-all-learner9: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y9 --- OK [0s]
=== START _one-vs-all-learner10: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y10
Accuracy = 1.60428% (30/1870)
=== END _one-vs-all-learner10: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y10 --- OK [1s]
=== START _one-vs-all-learner11: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y11
Accuracy = 3.36898% (63/1870)
=== END _one-vs-all-learner11: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y11 --- OK [0s]
=== START _one-vs-all-learner12: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y12
Accuracy = 2.72727% (51/1870)
=== END _one-vs-all-learner12: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y12 --- OK [1s]
=== START _one-vs-all-learner13: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y13
Accuracy = 1.44385% (27/1870)
=== END _one-vs-all-learner13: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y13 --- OK [0s]
=== START _one-vs-all-learner14: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y14
Accuracy = 1.60428% (30/1870)
=== END _one-vs-all-learner14: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y14 --- OK [1s]
=== START _one-vs-all-learner15: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y15
Accuracy = 1.17647% (22/1870)
=== END _one-vs-all-learner15: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y15 --- OK [0s]
=== START _one-vs-all-learner16: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y16
Accuracy = 9.25134% (173/1870)
=== END _one-vs-all-learner16: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y16 --- OK [1s]
=== START _one-vs-all-learner17: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y17
Accuracy = 2.13904% (40/1870)
=== END _one-vs-all-learner17: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y17 --- OK [0s]
=== START _one-vs-all-learner18: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y18
Accuracy = 2.83422% (53/1870)
=== END _one-vs-all-learner18: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y18 --- OK [1s]
=== START _one-vs-all-learner19: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y19
Accuracy = 5.45455% (102/1870)
=== END _one-vs-all-learner19: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y19 --- OK [0s]
=== START _one-vs-all-learner20: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y20
Accuracy = 6.84492% (128/1870)
=== END _one-vs-all-learner20: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y20 --- OK [1s]
=== START _one-vs-all-learner21: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y21
Accuracy = 3.04813% (57/1870)
=== END _one-vs-all-learner21: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y21 --- OK [0s]
=== START _one-vs-all-learner22: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y22
Accuracy = 2.72727% (51/1870)
=== END _one-vs-all-learner22: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y22 --- OK [1s]
=== START _one-vs-all-learner23: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y23
Accuracy = 2.24599% (42/1870)
=== END _one-vs-all-learner23: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y23 --- OK [0s]
=== START _one-vs-all-learner24: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y24
Accuracy = 0.641711% (12/1870)
=== END _one-vs-all-learner24: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y24 --- OK [1s]
=== START _one-vs-all-learner25: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y25
Accuracy = 2.51337% (47/1870)
=== END _one-vs-all-learner25: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y25 --- OK [0s]
=== START _one-vs-all-learner26: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y26
Accuracy = 5.34759% (100/1870)
=== END _one-vs-all-learner26: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y26 --- OK [1s]
=== START _one-vs-all-learner27: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y27
Accuracy = 4.06417% (76/1870)
=== END _one-vs-all-learner27: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y27 --- OK [0s]
1870 examples
=== END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [15s]
=== START program5: ./run evaluate ../dataset3/train ../program0/evalTrain.out
=== END program5: ./run evaluate ../dataset3/train ../program0/evalTrain.out --- OK [0s]

===== MAIN: predict/evaluate on test data =====
=== START program4: ./run stripLabels ../dataset3/test ../program0/evalTest.in
=== END program4: ./run stripLabels ../dataset3/test ../program0/evalTest.in --- OK [1s]
=== START program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out
=== START _one-vs-all-learner1: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y1
Accuracy = 1.74782% (14/801)
=== END _one-vs-all-learner1: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y1 --- OK [0s]
=== START _one-vs-all-learner2: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y2
Accuracy = 1.1236% (9/801)
=== END _one-vs-all-learner2: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y2 --- OK [0s]
=== START _one-vs-all-learner3: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y3
Accuracy = 7.99001% (64/801)
=== END _one-vs-all-learner3: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y3 --- OK [1s]
=== START _one-vs-all-learner4: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y4
Accuracy = 1.9975% (16/801)
=== END _one-vs-all-learner4: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y4 --- OK [0s]
=== START _one-vs-all-learner5: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y5
Accuracy = 0.499376% (4/801)
=== END _one-vs-all-learner5: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y5 --- OK [0s]
=== START _one-vs-all-learner6: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y6
Accuracy = 2.24719% (18/801)
=== END _one-vs-all-learner6: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y6 --- OK [0s]
=== START _one-vs-all-learner7: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y7
Accuracy = 11.3608% (91/801)
=== END _one-vs-all-learner7: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y7 --- OK [1s]
=== START _one-vs-all-learner8: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y8
Accuracy = 1.62297% (13/801)
=== END _one-vs-all-learner8: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y8 --- OK [0s]
=== START _one-vs-all-learner9: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y9
Accuracy = 1.24844% (10/801)
=== END _one-vs-all-learner9: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y9 --- OK [0s]
=== START _one-vs-all-learner10: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y10
Accuracy = 0.998752% (8/801)
=== END _one-vs-all-learner10: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y10 --- OK [0s]
=== START _one-vs-all-learner11: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y11
Accuracy = 3.74532% (30/801)
=== END _one-vs-all-learner11: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y11 --- OK [0s]
=== START _one-vs-all-learner12: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y12
Accuracy = 1.9975% (16/801)
=== END _one-vs-all-learner12: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y12 --- OK [1s]
=== START _one-vs-all-learner13: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y13
Accuracy = 0.249688% (2/801)
=== END _one-vs-all-learner13: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y13 --- OK [0s]
=== START _one-vs-all-learner14: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y14
Accuracy = 1.74782% (14/801)
=== END _one-vs-all-learner14: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y14 --- OK [0s]
=== START _one-vs-all-learner15: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y15
Accuracy = 1.24844% (10/801)
=== END _one-vs-all-learner15: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y15 --- OK [0s]
=== START _one-vs-all-learner16: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y16
Accuracy = 7.86517% (63/801)
=== END _one-vs-all-learner16: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y16 --- OK [1s]
=== START _one-vs-all-learner17: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y17
Accuracy = 2.24719% (18/801)
=== END _one-vs-all-learner17: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y17 --- OK [0s]
=== START _one-vs-all-learner18: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y18
Accuracy = 2.49688% (20/801)
=== END _one-vs-all-learner18: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y18 --- OK [0s]
=== START _one-vs-all-learner19: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y19
Accuracy = 5.61798% (45/801)
=== END _one-vs-all-learner19: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y19 --- OK [0s]
=== START _one-vs-all-learner20: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y20
Accuracy = 6.2422% (50/801)
=== END _one-vs-all-learner20: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y20 --- OK [1s]
=== START _one-vs-all-learner21: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y21
Accuracy = 2.49688% (20/801)
=== END _one-vs-all-learner21: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y21 --- OK [0s]
=== START _one-vs-all-learner22: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y22
Accuracy = 4.11985% (33/801)
=== END _one-vs-all-learner22: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y22 --- OK [0s]
=== START _one-vs-all-learner23: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y23
Accuracy = 1.74782% (14/801)
=== END _one-vs-all-learner23: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y23 --- OK [0s]
=== START _one-vs-all-learner24: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y24
Accuracy = 0.374532% (3/801)
=== END _one-vs-all-learner24: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y24 --- OK [1s]
=== START _one-vs-all-learner25: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y25
Accuracy = 4.11985% (33/801)
=== END _one-vs-all-learner25: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y25 --- OK [0s]
=== START _one-vs-all-learner26: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y26
Accuracy = 5.1186% (41/801)
=== END _one-vs-all-learner26: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y26 --- OK [0s]
=== START _one-vs-all-learner27: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y27
Accuracy = 4.74407% (38/801)
=== END _one-vs-all-learner27: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y27 --- OK [0s]
801 examples
=== END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [6s]
=== START program5: ./run evaluate ../dataset3/test ../program0/evalTest.out
=== END program5: ./run evaluate ../dataset3/test ../program0/evalTest.out --- OK [0s]


real	15m26.402s
user	5m43.357s
sys	0m2.128s

Run specification

Results

doTest:
- evaluate:
  - errorRate: 0.424469413233458
  - numErrors: 340
  - numExamples: 801
  - success: true
  - time: 0
- predict:
  - predict1:
    - success: true
    - time: 0
  - predict10:
    - success: true
    - time: 0
  - predict11:
    - success: true
    - time: 0
  - predict12:
    - success: true
    - time: 1
  - predict13:
    - success: true
    - time: 0
  - predict14:
    - success: true
    - time: 0
  - predict15:
    - success: true
    - time: 0
  - predict16:
    - success: true
    - time: 1
  - predict17:
    - success: true
    - time: 0
  - predict18:
    - success: true
    - time: 0
  - predict19:
    - success: true
    - time: 0
  - predict2:
    - success: true
    - time: 0
  - predict20:
    - success: true
    - time: 1
  - predict21:
    - success: true
    - time: 0
  - predict22:
    - success: true
    - time: 0
  - predict23:
    - success: true
    - time: 0
  - predict24:
    - success: true
    - time: 1
  - predict25:
    - success: true
    - time: 0
  - predict26:
    - success: true
    - time: 0
  - predict27:
    - success: true
    - time: 0
  - predict3:
    - success: true
    - time: 1
  - predict4:
    - success: true
    - time: 0
  - predict5:
    - success: true
    - time: 0
  - predict6:
    - success: true
    - time: 0
  - predict7:
    - success: true
    - time: 1
  - predict8:
    - success: true
    - time: 0
  - predict9:
    - success: true
    - time: 0
  - success: true
  - time: 6
- strip:
  - success: true
  - time: 1
doTrain:
- evaluate:
  - errorRate: 0.150802139037433
  - numErrors: 282
  - numExamples: 1870
  - success: true
  - time: 0
- predict:
  - predict1:
    - success: true
    - time: 0
  - predict10:
    - success: true
    - time: 1
  - predict11:
    - success: true
    - time: 0
  - predict12:
    - success: true
    - time: 1
  - predict13:
    - success: true
    - time: 0
  - predict14:
    - success: true
    - time: 1
  - predict15:
    - success: true
    - time: 0
  - predict16:
    - success: true
    - time: 1
  - predict17:
    - success: true
    - time: 0
  - predict18:
    - success: true
    - time: 1
  - predict19:
    - success: true
    - time: 0
  - predict2:
    - success: true
    - time: 1
  - predict20:
    - success: true
    - time: 1
  - predict21:
    - success: true
    - time: 0
  - predict22:
    - success: true
    - time: 1
  - predict23:
    - success: true
    - time: 0
  - predict24:
    - success: true
    - time: 1
  - predict25:
    - success: true
    - time: 0
  - predict26:
    - success: true
    - time: 1
  - predict27:
    - success: true
    - time: 0
  - predict3:
    - success: true
    - time: 0
  - predict4:
    - success: true
    - time: 1
  - predict5:
    - success: true
    - time: 0
  - predict6:
    - success: true
    - time: 1
  - predict7:
    - success: true
    - time: 0
  - predict8:
    - success: true
    - time: 1
  - predict9:
    - success: true
    - time: 0
  - success: true
  - time: 15
- strip:
  - success: true
  - time: 0
exitCode: 0
learn:
- learn1:
  - success: true
  - time: 6
- learn10:
  - success: true
  - time: 32
- learn11:
  - success: true
  - time: 32
- learn12:
  - success: true
  - time: 43
- learn13:
  - success: true
  - time: 19
- learn14:
  - success: true
  - time: 13
- learn15:
  - success: true
  - time: 5
- learn16:
  - success: true
  - time: 70
- learn17:
  - success: true
  - time: 15
- learn18:
  - success: true
  - time: 101
- learn19:
  - success: true
  - time: 54
- learn2:
  - success: true
  - time: 6
- learn20:
  - success: true
  - time: 70
- learn21:
  - success: true
  - time: 25
- learn22:
  - success: true
  - time: 146
- learn23:
  - success: true
  - time: 24
- learn24:
  - success: true
  - time: 3
- learn25:
  - success: true
  - time: 44
- learn26:
  - success: true
  - time: 52
- learn27:
  - success: true
  - time: 2
- learn3:
  - success: true
  - time: 20
- learn4:
  - success: true
  - time: 21
- learn5:
  - success: true
  - time: 8
- learn6:
  - success: true
  - time: 6
- learn7:
  - success: true
  - time: 16
- learn8:
  - success: true
  - time: 18
- learn9:
  - success: true
  - time: 38
- success: true
- time: 897
success: true

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MLcomp version alpha Statistics: 2040 users, 645 datasets, 389 programs, 18768 runs (0 queued, 3 running), 1 workers

Log file

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