ServerRun 39481
Creatorchuertas
ProgramMoPe
DatasetLos tres mosqueteros
Task typeBinaryClassification
Created2y182d ago
Done! Flag_green
6s
31M
MulticlassClassification
2s
0.945
1s
0.954
1s

Log file

===== 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
../data1
Number of TrainExamples=7354 , Number of TrainFeatures=160 , MaxTrainFeaturesId=162
Positive examples=406
Negative examples=6948
*************************
iterations=25
maxF1=0.158985	TP=257	FP=2570	FN=149	TN=4378

WallTime=0.68 sec

=== END _one-vs-all-learner1: ./run learn ../data1 --- OK [1s]

===== One versus all: training label y=2 versus the rest =====
=== START _one-vs-all-learner2: ./run learn ../data2
../data2
Number of TrainExamples=7354 , Number of TrainFeatures=160 , MaxTrainFeaturesId=162
Positive examples=6948
Negative examples=406
*************************
iterations=25
maxF1=0.770581	TP=4479	FP=198	FN=2469	TN=208

WallTime=0.69 sec

=== END _one-vs-all-learner2: ./run learn ../data2 --- OK [0s]

=== END program1: ./run learn ../dataset3/train --- OK [2s]

===== 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
../../program0/evalTrain.in
Number of TestExamples=7354 , Number of TestFeatures=160 , MaxTestFeaturesId=162
F1=0.555348	TP=2827	FN=4527	FP=0	TN=0

	Detailed Evaluation
---------------------------------------
Accuracy                 =38.4417
Precision                =100
Recall                   =38.4417
F(1)                     =55.5348
BEP (PR break even point)=0
Area Under ROC Curve     =-nan
Area Under PR Curve      =82.9209
Average Precision        =100

WallTime=0.56 sec

=== 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
../../program0/evalTrain.in
Number of TestExamples=7354 , Number of TestFeatures=160 , MaxTestFeaturesId=162
F1=0.777491	TP=4677	FN=2677	FP=0	TN=0

	Detailed Evaluation
---------------------------------------
Accuracy                 =63.598
Precision                =100
Recall                   =63.598
F(1)                     =77.7491
BEP (PR break even point)=0
Area Under ROC Curve     =-nan
Area Under PR Curve      =82.9209
Average Precision        =100

WallTime=0.60 sec

=== END _one-vs-all-learner2: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y2 --- OK [1s]
7354 examples
=== END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [1s]
=== START program5: ./run evaluate ../dataset3/train ../program0/evalTrain.out
=== END program5: ./run evaluate ../dataset3/train ../program0/evalTrain.out --- OK [1s]

===== 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 [0s]
=== START program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out
=== START _one-vs-all-learner1: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y1
../../program0/evalTest.in
Number of TestExamples=3152 , Number of TestFeatures=158 , MaxTestFeaturesId=162
F1=0.553133	TP=1205	FN=1947	FP=0	TN=0

	Detailed Evaluation
---------------------------------------
Accuracy                 =38.2297
Precision                =100
Recall                   =38.2297
F(1)                     =55.3133
BEP (PR break even point)=0
Area Under ROC Curve     =-nan
Area Under PR Curve      =88.9594
Average Precision        =100

WallTime=0.24 sec

=== END _one-vs-all-learner1: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y1 --- OK [1s]
=== START _one-vs-all-learner2: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y2
../../program0/evalTest.in
Number of TestExamples=3152 , Number of TestFeatures=158 , MaxTestFeaturesId=162
F1=0.76899	TP=1969	FN=1183	FP=0	TN=0

	Detailed Evaluation
---------------------------------------
Accuracy                 =62.4683
Precision                =100
Recall                   =62.4683
F(1)                     =76.899
BEP (PR break even point)=0
Area Under ROC Curve     =-nan
Area Under PR Curve      =88.9594
Average Precision        =100

WallTime=0.24 sec

=== END _one-vs-all-learner2: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y2 --- OK [0s]
3152 examples
=== END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [1s]
=== START program5: ./run evaluate ../dataset3/test ../program0/evalTest.out
=== END program5: ./run evaluate ../dataset3/test ../program0/evalTest.out --- OK [0s]


real	0m6.697s
user	0m5.176s
sys	0m1.072s

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