Status: Done!
Total Time
10s
Max Memory Usage
51M
Domain
BinaryClassification
Learn time
Train error
0.102
Predict train time
Test error
0.096
Predict test time
Log file
... (lines omitted) ...
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=== END program2: ./run learn ../program1/data --- OK [1s]
=== END program1: ./run learn ../dataset3/train --- OK [1s]
===== 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 program2: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out.multiclass-output
=== END program2: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out.multiclass-output --- OK [0s]
=== END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [0s]
=== 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 [0s]
=== START program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out
=== START program2: ./run predict ../program0/evalTest.in ../program0/evalTest.out.multiclass-output
=== END program2: ./run predict ../program0/evalTest.in ../program0/evalTest.out.multiclass-output --- OK [0s]
=== END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [0s]
=== START program5: ./run evaluate ../dataset3/test ../program0/evalTest.out
=== END program5: ./run evaluate ../dataset3/test ../program0/evalTest.out --- OK [1s]
real 0m15.950s
user 0m5.896s
sys 0m0.744s
supervised-learning : Main entry for supervised learning for training and testing a program on a dataset.
(learner:Program) binary-to-multi : Allows multiclass classification to be run on binary classification datasets (trivial reduction).
(multiclassLearner:Program[MulticlassClassification]) minimalist-boost : Minimalist implementation of boostexter's "scored-text" threshold-based weak learners. Source code included.
(dataset:Dataset) binary-guessing-2 :
(stripper:Program[Strip]) binary-utils : Validates and inspects a dataset in BinaryClassification format.
(evaluator:Program[Evaluate]) classification-evaluator : Evaluates predictions of classification datasets (discrete outputs).
doTest:
evaluate:
errorRate: 0.0964912280701754
numErrors: 11
numExamples: 114
success: true
time: 1
predict:
predict:
success: true
time: 0
strip:
doTrain:
evaluate:
errorRate: 0.101503759398496
numErrors: 27
numExamples: 266
success: true
time: 0
predict:
predict:
success: true
time: 0
strip:
exitCode: 0
learn:
learn:
success: true
time: 1
success: true
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