MLcomp version alpha Statistics: 1407 users, 462 datasets, 360 programs, 16683 runs (0 queued, 1 running), 10 workers

Run 790

Creator	pliang
Program	simple-naive-bayes
Dataset	svmlight-example1
Task type	MulticlassClassification
Created	31d15h ago
Download	Login required!

Status: Done!

Total Time	11s
Max Memory Usage	45M
Domain	BinaryClassification
Learn time	10s
Train error	0.019
Predict train time	1s
Test error	0.037
Predict test time	0s

Log file

=== Starting: cd /home/mlcomp/worker1/scratch/program0/../program1 && ./run learn '/home/mlcomp/worker1/scratch/program0/../dataset6/train'
=== Starting: cd /home/mlcomp/worker1/scratch/program1/../program4 && ./run split '/home/mlcomp/worker1/scratch/program0/../dataset6/train' '/home/mlcomp/worker1/scratch/program1/cv.train' '/home/mlcomp/worker1/scratch/program1/cv.test'
=== Finished: cd /home/mlcomp/worker1/scratch/program1/../program4 && ./run split '/home/mlcomp/worker1/scratch/program0/../dataset6/train' '/home/mlcomp/worker1/scratch/program1/cv.train' '/home/mlcomp/worker1/scratch/program1/cv.test' --- OK [0s]
=== Starting: cd _tune-hyperparameter0 && ./run setHyperparameter '0.01'
Saving hyperparameter 0.01
=== Finished: cd _tune-hyperparameter0 && ./run setHyperparameter '0.01' --- OK [0s]
=== Starting: cd _tune-hyperparameter0 && ./run learn '/home/mlcomp/worker1/scratch/program1/cv.train'
Processing training examples...
Smoothing and normalizing (reverse = false)...
Saving model...
=== Finished: cd _tune-hyperparameter0 && ./run learn '/home/mlcomp/worker1/scratch/program1/cv.train' --- OK [1s]
=== Starting: cd _tune-hyperparameter0 && ./run predict '/home/mlcomp/worker1/scratch/program1/cv.test' '/home/mlcomp/worker1/scratch/program1/cvTestPredictions0'
Loading model...
Predicting test examples...
=== Finished: cd _tune-hyperparameter0 && ./run predict '/home/mlcomp/worker1/scratch/program1/cv.test' '/home/mlcomp/worker1/scratch/program1/cvTestPredictions0' --- OK [1s]
=== Starting: cd /home/mlcomp/worker1/scratch/program1/../program5 && ./run evaluate '/home/mlcomp/worker1/scratch/program1/cv.test' '/home/mlcomp/worker1/scratch/program1/cvTestPredictions0'
=== Finished: cd /home/mlcomp/worker1/scratch/program1/../program5 && ./run evaluate '/home/mlcomp/worker1/scratch/program1/cv.test' '/home/mlcomp/worker1/scratch/program1/cvTestPredictions0' --- OK [0s]
CV error rate 0.043261231281198 with hyperparameter 0.01
=== Starting: cd _tune-hyperparameter1 && ./run setHyperparameter '0.1'
Saving hyperparameter 0.1
=== Finished: cd _tune-hyperparameter1 && ./run setHyperparameter '0.1' --- OK [0s]
=== Starting: cd _tune-hyperparameter1 && ./run learn '/home/mlcomp/worker1/scratch/program1/cv.train'
Processing training examples...
Smoothing and normalizing (reverse = false)...
Saving model...
=== Finished: cd _tune-hyperparameter1 && ./run learn '/home/mlcomp/worker1/scratch/program1/cv.train' --- OK [1s]
=== Starting: cd _tune-hyperparameter1 && ./run predict '/home/mlcomp/worker1/scratch/program1/cv.test' '/home/mlcomp/worker1/scratch/program1/cvTestPredictions1'
Loading model...
Predicting test examples...
=== Finished: cd _tune-hyperparameter1 && ./run predict '/home/mlcomp/worker1/scratch/program1/cv.test' '/home/mlcomp/worker1/scratch/program1/cvTestPredictions1' --- OK [1s]
=== Starting: cd /home/mlcomp/worker1/scratch/program1/../program5 && ./run evaluate '/home/mlcomp/worker1/scratch/program1/cv.test' '/home/mlcomp/worker1/scratch/program1/cvTestPredictions1'
=== Finished: cd /home/mlcomp/worker1/scratch/program1/../program5 && ./run evaluate '/home/mlcomp/worker1/scratch/program1/cv.test' '/home/mlcomp/worker1/scratch/program1/cvTestPredictions1' --- OK [0s]
CV error rate 0.0382695507487521 with hyperparameter 0.1
=== Starting: cd _tune-hyperparameter2 && ./run setHyperparameter '1.0'
Saving hyperparameter 1.0
=== Finished: cd _tune-hyperparameter2 && ./run setHyperparameter '1.0' --- OK [0s]
=== Starting: cd _tune-hyperparameter2 && ./run learn '/home/mlcomp/worker1/scratch/program1/cv.train'
Processing training examples...
Smoothing and normalizing (reverse = false)...
Saving model...
=== Finished: cd _tune-hyperparameter2 && ./run learn '/home/mlcomp/worker1/scratch/program1/cv.train' --- OK [1s]
=== Starting: cd _tune-hyperparameter2 && ./run predict '/home/mlcomp/worker1/scratch/program1/cv.test' '/home/mlcomp/worker1/scratch/program1/cvTestPredictions2'
Loading model...
Predicting test examples...
=== Finished: cd _tune-hyperparameter2 && ./run predict '/home/mlcomp/worker1/scratch/program1/cv.test' '/home/mlcomp/worker1/scratch/program1/cvTestPredictions2' --- OK [1s]
=== Starting: cd /home/mlcomp/worker1/scratch/program1/../program5 && ./run evaluate '/home/mlcomp/worker1/scratch/program1/cv.test' '/home/mlcomp/worker1/scratch/program1/cvTestPredictions2'
=== Finished: cd /home/mlcomp/worker1/scratch/program1/../program5 && ./run evaluate '/home/mlcomp/worker1/scratch/program1/cv.test' '/home/mlcomp/worker1/scratch/program1/cvTestPredictions2' --- OK [0s]
CV error rate 0.0399334442595674 with hyperparameter 1.0
=== Starting: cd _tune-hyperparameter3 && ./run setHyperparameter '10.0'
Saving hyperparameter 10.0
=== Finished: cd _tune-hyperparameter3 && ./run setHyperparameter '10.0' --- OK [0s]
=== Starting: cd _tune-hyperparameter3 && ./run learn '/home/mlcomp/worker1/scratch/program1/cv.train'
Processing training examples...
Smoothing and normalizing (reverse = false)...
Saving model...
=== Finished: cd _tune-hyperparameter3 && ./run learn '/home/mlcomp/worker1/scratch/program1/cv.train' --- OK [1s]
=== Starting: cd _tune-hyperparameter3 && ./run predict '/home/mlcomp/worker1/scratch/program1/cv.test' '/home/mlcomp/worker1/scratch/program1/cvTestPredictions3'
Loading model...
Predicting test examples...
=== Finished: cd _tune-hyperparameter3 && ./run predict '/home/mlcomp/worker1/scratch/program1/cv.test' '/home/mlcomp/worker1/scratch/program1/cvTestPredictions3' --- OK [1s]
=== Starting: cd /home/mlcomp/worker1/scratch/program1/../program5 && ./run evaluate '/home/mlcomp/worker1/scratch/program1/cv.test' '/home/mlcomp/worker1/scratch/program1/cvTestPredictions3'
=== Finished: cd /home/mlcomp/worker1/scratch/program1/../program5 && ./run evaluate '/home/mlcomp/worker1/scratch/program1/cv.test' '/home/mlcomp/worker1/scratch/program1/cvTestPredictions3' --- OK [0s]
CV error rate 0.0382695507487521 with hyperparameter 10.0
=== Starting: cd _tune-hyperparameter4 && ./run setHyperparameter '100.0'
Saving hyperparameter 100.0
=== Finished: cd _tune-hyperparameter4 && ./run setHyperparameter '100.0' --- OK [0s]
=== Starting: cd _tune-hyperparameter4 && ./run learn '/home/mlcomp/worker1/scratch/program1/cv.train'
Processing training examples...
Smoothing and normalizing (reverse = false)...
Saving model...
=== Finished: cd _tune-hyperparameter4 && ./run learn '/home/mlcomp/worker1/scratch/program1/cv.train' --- OK [1s]
=== Starting: cd _tune-hyperparameter4 && ./run predict '/home/mlcomp/worker1/scratch/program1/cv.test' '/home/mlcomp/worker1/scratch/program1/cvTestPredictions4'
Loading model...
Predicting test examples...
=== Finished: cd _tune-hyperparameter4 && ./run predict '/home/mlcomp/worker1/scratch/program1/cv.test' '/home/mlcomp/worker1/scratch/program1/cvTestPredictions4' --- OK [0s]
=== Starting: cd /home/mlcomp/worker1/scratch/program1/../program5 && ./run evaluate '/home/mlcomp/worker1/scratch/program1/cv.test' '/home/mlcomp/worker1/scratch/program1/cvTestPredictions4'
=== Finished: cd /home/mlcomp/worker1/scratch/program1/../program5 && ./run evaluate '/home/mlcomp/worker1/scratch/program1/cv.test' '/home/mlcomp/worker1/scratch/program1/cvTestPredictions4' --- OK [1s]
CV error rate 0.0582362728785358 with hyperparameter 100.0
Best hyperparameter value is 0.1; got CV error rate 0.0382695507487521
=== Finished: cd /home/mlcomp/worker1/scratch/program0/../program1 && ./run learn '/home/mlcomp/worker1/scratch/program0/../dataset6/train' --- OK [10s]
=== Starting: cd /home/mlcomp/worker1/scratch/program0/../program7 && ./run stripLabels '/home/mlcomp/worker1/scratch/program0/../dataset6/train' '/home/mlcomp/worker1/scratch/program0/evalTrain.in'
=== Finished: cd /home/mlcomp/worker1/scratch/program0/../program7 && ./run stripLabels '/home/mlcomp/worker1/scratch/program0/../dataset6/train' '/home/mlcomp/worker1/scratch/program0/evalTrain.in' --- OK [0s]
=== Starting: cd /home/mlcomp/worker1/scratch/program0/../program1 && ./run predict '/home/mlcomp/worker1/scratch/program0/evalTrain.in' '/home/mlcomp/worker1/scratch/program0/evalTrain.out'
=== Starting: cd _tune-hyperparameter-best && ./run predict '/home/mlcomp/worker1/scratch/program0/evalTrain.in' '/home/mlcomp/worker1/scratch/program0/evalTrain.out'
Loading model...
Predicting test examples...
=== Finished: cd _tune-hyperparameter-best && ./run predict '/home/mlcomp/worker1/scratch/program0/evalTrain.in' '/home/mlcomp/worker1/scratch/program0/evalTrain.out' --- OK [1s]
=== Finished: cd /home/mlcomp/worker1/scratch/program0/../program1 && ./run predict '/home/mlcomp/worker1/scratch/program0/evalTrain.in' '/home/mlcomp/worker1/scratch/program0/evalTrain.out' --- OK [1s]
=== Starting: cd /home/mlcomp/worker1/scratch/program0/../program8 && ./run evaluate '/home/mlcomp/worker1/scratch/program0/../dataset6/train' '/home/mlcomp/worker1/scratch/program0/evalTrain.out'
=== Finished: cd /home/mlcomp/worker1/scratch/program0/../program8 && ./run evaluate '/home/mlcomp/worker1/scratch/program0/../dataset6/train' '/home/mlcomp/worker1/scratch/program0/evalTrain.out' --- OK [0s]
=== Starting: cd /home/mlcomp/worker1/scratch/program0/../program7 && ./run stripLabels '/home/mlcomp/worker1/scratch/program0/../dataset6/test' '/home/mlcomp/worker1/scratch/program0/evalTest.in'
=== Finished: cd /home/mlcomp/worker1/scratch/program0/../program7 && ./run stripLabels '/home/mlcomp/worker1/scratch/program0/../dataset6/test' '/home/mlcomp/worker1/scratch/program0/evalTest.in' --- OK [0s]
=== Starting: cd /home/mlcomp/worker1/scratch/program0/../program1 && ./run predict '/home/mlcomp/worker1/scratch/program0/evalTest.in' '/home/mlcomp/worker1/scratch/program0/evalTest.out'
=== Starting: cd _tune-hyperparameter-best && ./run predict '/home/mlcomp/worker1/scratch/program0/evalTest.in' '/home/mlcomp/worker1/scratch/program0/evalTest.out'
Loading model...
Predicting test examples...
=== Finished: cd _tune-hyperparameter-best && ./run predict '/home/mlcomp/worker1/scratch/program0/evalTest.in' '/home/mlcomp/worker1/scratch/program0/evalTest.out' --- OK [0s]
=== Finished: cd /home/mlcomp/worker1/scratch/program0/../program1 && ./run predict '/home/mlcomp/worker1/scratch/program0/evalTest.in' '/home/mlcomp/worker1/scratch/program0/evalTest.out' --- OK [0s]
=== Starting: cd /home/mlcomp/worker1/scratch/program0/../program8 && ./run evaluate '/home/mlcomp/worker1/scratch/program0/../dataset6/test' '/home/mlcomp/worker1/scratch/program0/evalTest.out'
=== Finished: cd /home/mlcomp/worker1/scratch/program0/../program8 && ./run evaluate '/home/mlcomp/worker1/scratch/program0/../dataset6/test' '/home/mlcomp/worker1/scratch/program0/evalTest.out' --- OK [0s]

real	0m12.458s
user	0m10.489s
sys	0m1.440s

Run specification

• 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]) tune-hyperparameter: Sets the hyperparameter
      • (numProbes:int) 5
      • (learner:Program) simple-naive-bayes: A Simple Naive Bayes implementation in Ruby.
      • (splitter:Program) multiclass-utils: Validates and inspects a dataset in MulticlassClassification format.
      • (evaluator:Program[Evaluate]) classification-evaluator: Evaluates predictions of classification datasets (discrete outputs).
  • (dataset:Dataset) svmlight-example1: Example 1 from SVMlight software
  • (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).

Results

• doTest:
  • evaluate:
    • errorRate: 0.0366666666666667
    • numErrors: 22
    • numExamples: 600
    • success: true
    • time: 0
  • predict:
    • predict:
      • success: true
      • time: 0
    • success: true
    • time: 0
  • strip:
    • success: true
    • time: 0
• doTrain:
  • evaluate:
    • errorRate: 0.019
    • numErrors: 38
    • numExamples: 2000
    • success: true
    • time: 0
  • predict:
    • predict:
      • success: true
      • time: 1
    • success: true
    • time: 1
  • strip:
    • success: true
    • time: 0
• exitCode: 0
• learn:
  • bestCVErrorRate: 0.0382695507487521
  • bestHyperparameter: 0.1
  • evaluate0:
    • errorRate: 0.043261231281198
    • numErrors: 26
    • numExamples: 601
    • success: true
    • time: 0
  • evaluate1:
    • errorRate: 0.0382695507487521
    • numErrors: 23
    • numExamples: 601
    • success: true
    • time: 0
  • evaluate2:
    • errorRate: 0.0399334442595674
    • numErrors: 24
    • numExamples: 601
    • success: true
    • time: 0
  • evaluate3:
    • errorRate: 0.0382695507487521
    • numErrors: 23
    • numExamples: 601
    • success: true
    • time: 0
  • evaluate4:
    • errorRate: 0.0582362728785358
    • numErrors: 35
    • numExamples: 601
    • success: true
    • time: 1
  • learn0:
    • success: true
    • time: 1
  • learn1:
    • success: true
    • time: 1
  • learn2:
    • success: true
    • time: 1
  • learn3:
    • success: true
    • time: 1
  • learn4:
    • success: true
    • time: 1
  • predict0:
    • success: true
    • time: 1
  • predict1:
    • success: true
    • time: 1
  • predict2:
    • success: true
    • time: 1
  • predict3:
    • success: true
    • time: 1
  • predict4:
    • success: true
    • time: 0
  • setHyperparameter0:
    • success: true
    • time: 0
  • setHyperparameter1:
    • success: true
    • time: 0
  • setHyperparameter2:
    • success: true
    • time: 0
  • setHyperparameter3:
    • success: true
    • time: 0
  • setHyperparameter4:
    • success: true
    • time: 0
  • split:
    • success: true
    • time: 0
  • success: true
  • time: 10
• success: true

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