ServerRun 39342
Creatorartrey
Programliblinear-s6-B1
Datasetletter-recognition
Task typeBinaryClassification
Created2y63d ago
DownloadLogin required!
Done! Flag_green
7m39s
45M
MulticlassClassification
7m20s
0.608
7s
0.617
3s

Log file

... (lines omitted) ...
cc -Wall -Wconversion -O3 -fPIC  -c dscal.c
ar rcv blas.a dnrm2.o daxpy.o ddot.o dscal.o   
a - dnrm2.o
a - daxpy.o
a - ddot.o
a - dscal.o
ranlib  blas.a
make[1]: Leaving directory `/home/mlcomp/worker/scratch/program2/liblinear-1.51/blas'
g++ -Wall -Wconversion -O3 -fPIC -o train train.c tron.o linear.o blas/blas.a
g++ -Wall -Wconversion -O3 -fPIC -o predict predict.c tron.o linear.o blas/blas.a
===== MAIN: learn based on training data =====
=== START program1: ./run learn ../dataset3/train
===== One versus all: training label y=1 versus the rest =====
=== START _one-vs-all-learner1: ./run learn ../data1
..........
optimization finished, #iter = 100
Objective value = 509.666572
#nonzeros/#features = 17/17
=== END _one-vs-all-learner1: ./run learn ../data1 --- OK [9s]

===== One versus all: training label y=2 versus the rest =====
=== START _one-vs-all-learner2: ./run learn ../data2
................
optimization finished, #iter = 162
Objective value = 1315.288754
#nonzeros/#features = 17/17
=== END _one-vs-all-learner2: ./run learn ../data2 --- OK [14s]

===== One versus all: training label y=3 versus the rest =====
=== START _one-vs-all-learner3: ./run learn ../data3
.........................*.......
optimization finished, #iter = 326
Objective value = 1014.425013
#nonzeros/#features = 17/17
=== END _one-vs-all-learner3: ./run learn ../data3 --- OK [28s]

===== One versus all: training label y=4 versus the rest =====
=== START _one-vs-all-learner4: ./run learn ../data4
.........................
optimization finished, #iter = 258
Objective value = 1134.231526
#nonzeros/#features = 17/17
=== END _one-vs-all-learner4: ./run learn ../data4 --- OK [23s]

===== One versus all: training label y=5 versus the rest =====
=== START _one-vs-all-learner5: ./run learn ../data5
.....................
optimization finished, #iter = 218
Objective value = 1334.280716
#nonzeros/#features = 17/17
=== END _one-vs-all-learner5: ./run learn ../data5 --- OK [19s]

===== One versus all: training label y=6 versus the rest =====
=== START _one-vs-all-learner6: ./run learn ../data6
.....................
optimization finished, #iter = 215
Objective value = 1252.075313
#nonzeros/#features = 17/17
=== END _one-vs-all-learner6: ./run learn ../data6 --- OK [19s]

===== One versus all: training label y=7 versus the rest =====
=== START _one-vs-all-learner7: ./run learn ../data7
............................
optimization finished, #iter = 282
Objective value = 1800.020495
#nonzeros/#features = 17/17
=== END _one-vs-all-learner7: ./run learn ../data7 --- OK [23s]

===== One versus all: training label y=8 versus the rest =====
=== START _one-vs-all-learner8: ./run learn ../data8
..................
optimization finished, #iter = 185
Objective value = 1770.185005
#nonzeros/#features = 17/17
=== END _one-vs-all-learner8: ./run learn ../data8 --- OK [16s]

===== One versus all: training label y=9 versus the rest =====
=== START _one-vs-all-learner9: ./run learn ../data9
.............*.
optimization finished, #iter = 143
Objective value = 913.168999
#nonzeros/#features = 17/17
=== END _one-vs-all-learner9: ./run learn ../data9 --- OK [12s]

===== One versus all: training label y=10 versus the rest =====
=== START _one-vs-all-learner10: ./run learn ../data10
.................
optimization finished, #iter = 173
Objective value = 744.721676
#nonzeros/#features = 17/17
=== END _one-vs-all-learner10: ./run learn ../data10 --- OK [15s]

===== One versus all: training label y=11 versus the rest =====
=== START _one-vs-all-learner11: ./run learn ../data11
.......................
optimization finished, #iter = 231
Objective value = 1396.740737
#nonzeros/#features = 17/17
=== END _one-vs-all-learner11: ./run learn ../data11 --- OK [20s]

===== One versus all: training label y=12 versus the rest =====
=== START _one-vs-all-learner12: ./run learn ../data12
.........
optimization finished, #iter = 92
Objective value = 780.205691
#nonzeros/#features = 17/17
=== END _one-vs-all-learner12: ./run learn ../data12 --- OK [8s]

===== One versus all: training label y=13 versus the rest =====
=== START _one-vs-all-learner13: ./run learn ../data13
.........
optimization finished, #iter = 99
Objective value = 450.635565
#nonzeros/#features = 17/17
=== END _one-vs-all-learner13: ./run learn ../data13 --- OK [9s]

===== One versus all: training label y=14 versus the rest =====
=== START _one-vs-all-learner14: ./run learn ../data14
.................
optimization finished, #iter = 176
Objective value = 1361.885774
#nonzeros/#features = 17/17
=== END _one-vs-all-learner14: ./run learn ../data14 --- OK [15s]

===== One versus all: training label y=15 versus the rest =====
=== START _one-vs-all-learner15: ./run learn ../data15
...........*..
optimization finished, #iter = 132
Objective value = 2001.153558
#nonzeros/#features = 17/17
=== END _one-vs-all-learner15: ./run learn ../data15 --- OK [11s]

===== One versus all: training label y=16 versus the rest =====
=== START _one-vs-all-learner16: ./run learn ../data16
....................
optimization finished, #iter = 209
Objective value = 679.512668
#nonzeros/#features = 17/17
=== END _one-vs-all-learner16: ./run learn ../data16 --- OK [19s]

===== One versus all: training label y=17 versus the rest =====
=== START _one-vs-all-learner17: ./run learn ../data17
..................
optimization finished, #iter = 185
Objective value = 1428.704767
#nonzeros/#features = 17/17
=== END _one-vs-all-learner17: ./run learn ../data17 --- OK [16s]

===== One versus all: training label y=18 versus the rest =====
=== START _one-vs-all-learner18: ./run learn ../data18
..............
optimization finished, #iter = 147
Objective value = 1198.643141
#nonzeros/#features = 17/17
=== END _one-vs-all-learner18: ./run learn ../data18 --- OK [13s]

===== One versus all: training label y=19 versus the rest =====
=== START _one-vs-all-learner19: ./run learn ../data19
.............
optimization finished, #iter = 139
Objective value = 1416.085976
#nonzeros/#features = 17/17
=== END _one-vs-all-learner19: ./run learn ../data19 --- OK [13s]

===== One versus all: training label y=20 versus the rest =====
=== START _one-vs-all-learner20: ./run learn ../data20
.......................
optimization finished, #iter = 237
Objective value = 921.242472
#nonzeros/#features = 17/17
=== END _one-vs-all-learner20: ./run learn ../data20 --- OK [21s]

===== One versus all: training label y=21 versus the rest =====
=== START _one-vs-all-learner21: ./run learn ../data21
....................
optimization finished, #iter = 208
Objective value = 962.316197
#nonzeros/#features = 17/17
=== END _one-vs-all-learner21: ./run learn ../data21 --- OK [18s]

===== One versus all: training label y=22 versus the rest =====
=== START _one-vs-all-learner22: ./run learn ../data22
.......................
optimization finished, #iter = 237
Objective value = 1073.487441
#nonzeros/#features = 17/17
=== END _one-vs-all-learner22: ./run learn ../data22 --- OK [21s]

===== One versus all: training label y=23 versus the rest =====
=== START _one-vs-all-learner23: ./run learn ../data23
..........
optimization finished, #iter = 101
Objective value = 555.160213
#nonzeros/#features = 17/17
=== END _one-vs-all-learner23: ./run learn ../data23 --- OK [9s]

===== One versus all: training label y=24 versus the rest =====
=== START _one-vs-all-learner24: ./run learn ../data24
..................*
optimization finished, #iter = 185
Objective value = 1536.757872
#nonzeros/#features = 17/17
=== END _one-vs-all-learner24: ./run learn ../data24 --- OK [15s]

===== One versus all: training label y=25 versus the rest =====
=== START _one-vs-all-learner25: ./run learn ../data25
..................................
optimization finished, #iter = 341
Objective value = 806.846053
#nonzeros/#features = 17/17
=== END _one-vs-all-learner25: ./run learn ../data25 --- OK [30s]

===== One versus all: training label y=26 versus the rest =====
=== START _one-vs-all-learner26: ./run learn ../data26
....................
optimization finished, #iter = 207
Objective value = 719.785818
#nonzeros/#features = 17/17
=== END _one-vs-all-learner26: ./run learn ../data26 --- OK [18s]

=== END program1: ./run learn ../dataset3/train --- OK [440s]

===== 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 [1s]
=== 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 = 3.62857% (508/14000)
=== 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 = 1.32143% (185/14000)
=== END _one-vs-all-learner2: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y2 --- OK [0s]
=== START _one-vs-all-learner3: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y3
Accuracy = 2.17143% (304/14000)
=== 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 = 2.25% (315/14000)
=== END _one-vs-all-learner4: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y4 --- OK [0s]
=== START _one-vs-all-learner5: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y5
Accuracy = 1.20714% (169/14000)
=== 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 = 1.65% (231/14000)
=== END _one-vs-all-learner6: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y6 --- OK [0s]
=== START _one-vs-all-learner7: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y7
Accuracy = 0.0785714% (11/14000)
=== 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 = 0.171429% (24/14000)
=== END _one-vs-all-learner8: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y8 --- OK [0s]
=== START _one-vs-all-learner9: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y9
Accuracy = 2.45% (343/14000)
=== END _one-vs-all-learner9: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y9 --- OK [1s]
=== START _one-vs-all-learner10: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y10
Accuracy = 2.85714% (400/14000)
=== END _one-vs-all-learner10: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y10 --- OK [0s]
=== START _one-vs-all-learner11: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y11
Accuracy = 0.771429% (108/14000)
=== 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 = 2.94286% (412/14000)
=== END _one-vs-all-learner12: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y12 --- OK [0s]
=== START _one-vs-all-learner13: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y13
Accuracy = 3.67143% (514/14000)
=== 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 = 1.75% (245/14000)
=== 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 = 0.05% (7/14000)
=== 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 = 3.27857% (459/14000)
=== END _one-vs-all-learner16: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y16 --- OK [0s]
=== START _one-vs-all-learner17: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y17
Accuracy = 1.25% (175/14000)
=== 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 = 1.89286% (265/14000)
=== 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 = 1.18571% (166/14000)
=== 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 = 3.02857% (424/14000)
=== END _one-vs-all-learner20: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y20 --- OK [0s]
=== START _one-vs-all-learner21: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y21
Accuracy = 2.32143% (325/14000)
=== 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 = 2.4% (336/14000)
=== 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 = 3.57143% (500/14000)
=== 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 = 0.657143% (92/14000)
=== END _one-vs-all-learner24: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y24 --- OK [0s]
=== START _one-vs-all-learner25: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y25
Accuracy = 3.20714% (449/14000)
=== 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 = 2.95% (413/14000)
=== END _one-vs-all-learner26: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y26 --- OK [0s]
14000 examples
=== END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [7s]
=== 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 = 3.5% (210/6000)
=== 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 = 1.6% (96/6000)
=== 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 = 2.01667% (121/6000)
=== END _one-vs-all-learner3: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y3 --- OK [0s]
=== START _one-vs-all-learner4: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y4
Accuracy = 2.56667% (154/6000)
=== 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 = 1.05% (63/6000)
=== 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 = 1.78333% (107/6000)
=== 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 = 0.0666667% (4/6000)
=== END _one-vs-all-learner7: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y7 --- OK [0s]
=== START _one-vs-all-learner8: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y8
Accuracy = 0.216667% (13/6000)
=== END _one-vs-all-learner8: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y8 --- OK [1s]
=== START _one-vs-all-learner9: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y9
Accuracy = 3% (180/6000)
=== 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 = 3.21667% (193/6000)
=== 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 = 0.483333% (29/6000)
=== 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 = 2.63333% (158/6000)
=== END _one-vs-all-learner12: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y12 --- OK [0s]
=== START _one-vs-all-learner13: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y13
Accuracy = 3.73333% (224/6000)
=== 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 = 1.56667% (94/6000)
=== 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 = 0.0833333% (5/6000)
=== 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 = 3.08333% (185/6000)
=== END _one-vs-all-learner16: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y16 --- OK [0s]
=== START _one-vs-all-learner17: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y17
Accuracy = 1.23333% (74/6000)
=== END _one-vs-all-learner17: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y17 --- OK [1s]
=== START _one-vs-all-learner18: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y18
Accuracy = 1.96667% (118/6000)
=== 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 = 1.11667% (67/6000)
=== 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 = 3.08333% (185/6000)
=== END _one-vs-all-learner20: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y20 --- OK [0s]
=== START _one-vs-all-learner21: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y21
Accuracy = 2.45% (147/6000)
=== 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 = 2.33333% (140/6000)
=== 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 = 3.61667% (217/6000)
=== 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 = 0.833333% (50/6000)
=== END _one-vs-all-learner24: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y24 --- OK [0s]
=== START _one-vs-all-learner25: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y25
Accuracy = 2.96667% (178/6000)
=== END _one-vs-all-learner25: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y25 --- OK [1s]
=== START _one-vs-all-learner26: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y26
Accuracy = 2.66667% (160/6000)
=== END _one-vs-all-learner26: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y26 --- OK [0s]
6000 examples
=== END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [3s]
=== START program5: ./run evaluate ../dataset3/test ../program0/evalTest.out
=== END program5: ./run evaluate ../dataset3/test ../program0/evalTest.out --- OK [1s]


real	7m40.310s
user	7m22.200s
sys	0m5.316s

Run specification Arrow_right
Results Arrow_right


Comments:


Must be logged in to post comments.