Run
16055

Run 16055

Task 47 (Supervised Classification) tae Uploaded 04-06-2014 by Joaquin Vanschoren
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Flow

weka.MultiBoostAB_NaiveBayes(1)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.MultiBoostAB_NaiveBayes(1)_C3
weka.MultiBoostAB_NaiveBayes(1)_I20
weka.MultiBoostAB_NaiveBayes(1)_P100
weka.MultiBoostAB_NaiveBayes(1)_S1
weka.MultiBoostAB_NaiveBayes(1)_Wweka.classifiers.bayes.NaiveBayes

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

19 Evaluation measures

Area under ROC curve
0.6529
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.5265
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.2964
Cross-validation details (10-fold Crossvalidation)
KB relative information score
23.2719
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.4071
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4443
Cross-validation details (10-fold Crossvalidation)
Number of instances
151
Per class
Cross-validation details (10-fold Crossvalidation)
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.5387
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.5298
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.5845
Cross-validation details (10-fold Crossvalidation)
Recall
0.5298
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9162
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4713
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4542
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9636
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
923.4438[563.7494238588241898.3473310650888483.23216931738307912.43991219425081759.4501199261804]