MLcomp version alpha Statistics: 2046 users, 665 datasets, 389 programs, 18920 runs (0 queued, 4 running), 0 workers

Run 27515

Creator	evolk
Program	BayesNet_weka_nominal
Dataset	epetals_2_lr5
Task type	MulticlassClassification
Created	285d7h ago

Status: Done!

Total Time	21m47s
Max Memory Usage	767M
Domain	MulticlassClassification
Learn time	10m2s
Train error	0.294
Predict train time	8m26s
Test error	0.291
Predict test time	2m50s

Log file

Note: Some input files use unchecked or unsafe operations.
Note: Recompile with -Xlint:unchecked for details.
MulticlassClassification
===== MAIN: learn based on training data =====
=== START program1: ./run learn ../dataset2/train
Warning: discretizing data set
MulticlassClassification
=== END program1: ./run learn ../dataset2/train --- OK [602s]

===== MAIN: predict/evaluate on train data =====
=== START program3: ./run stripLabels ../dataset2/train ../program0/evalTrain.in
=== END program3: ./run stripLabels ../dataset2/train ../program0/evalTrain.in --- OK [4s]
=== START program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out
MulticlassClassification
=== END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [506s]
=== START program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out
=== END program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out --- OK [10s]

===== MAIN: predict/evaluate on test data =====
=== START program3: ./run stripLabels ../dataset2/test ../program0/evalTest.in
=== END program3: ./run stripLabels ../dataset2/test ../program0/evalTest.in --- OK [2s]
=== START program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out
MulticlassClassification
=== END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [170s]
=== START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out
=== END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [4s]


real	21m48.579s
user	20m45.766s
sys	0m34.850s

Run specification

• supervised-learning: Main entry for supervised learning for training and testing a program on a dataset.
  • (learner:Program) BayesNet_weka_nominal: This programs is part of the WEKA classifier library. The code used to generate this program is from the java class 'weka/classifiers/bayes/BayesNet.java' from WEKA's libraries. The following description was taken from this classes JavaDoc information:
    
    ---------------------
    Bayes Network learning using various search algorithms and quality measures. Base class for a Bayes Network classifier. Provides datastructures (network structure, conditional probability distributions, etc.) and facilities common to Bayes Network learning algorithms like K2 and B. For more information see: http://www.cs.waikato.ac.nz/~remco/weka.pdf
    ---------------------
    
    NOTE: This algorithm has no parameter tuning, it is using the default WEKA parameters
    
    NOTE: WEKA's Classifiers read a data in the .arff format. For Multiclass datasets, the SVMlight format converted to .arff multiclass format so they can be read by WEKA programs
  • (dataset:Dataset) epetals_2_lr5:
  • (stripper:Program[Strip]) multiclass-utils: Validates and inspects a dataset in MulticlassClassification format.
  • (evaluator:Program[Evaluate]) classification-evaluator: Evaluates predictions of classification datasets (discrete outputs).

Results

• doTest:
  • evaluate:
    • errorRate: 0.290998276547793
    • numErrors: 4390
    • numExamples: 15086
    • success: true
    • time: 4
  • predict:
    • success: true
    • time: 170
  • strip:
    • success: true
    • time: 2
• doTrain:
  • evaluate:
    • errorRate: 0.293798471634329
    • numErrors: 10342
    • numExamples: 35201
    • success: true
    • time: 10
  • predict:
    • success: true
    • time: 506
  • strip:
    • success: true
    • time: 4
• exitCode: 0
• learn:
  • success: true
  • time: 602
• success: true

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