OpenML
19337

Run 19337

Task 16 (Supervised Classification) mfeat-karhunen Uploaded 12-06-2014 by Joaquin Vanschoren
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Flow

weka.MultiBoostAB_RandomTree(1)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.MultiBoostAB_RandomTree(1)_C3
weka.MultiBoostAB_RandomTree(1)_I10
weka.MultiBoostAB_RandomTree(1)_P100
weka.MultiBoostAB_RandomTree(1)_S1
weka.MultiBoostAB_RandomTree(1)_Wweka.classifiers.trees.RandomTree
weka.RandomTree(1)_K0
weka.RandomTree(1)_M1.0
weka.RandomTree(1)_S1

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
0.85
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7309
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.7
Cross-validation details (10-fold Crossvalidation)
KB relative information score
1435.291
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.054
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.18
Cross-validation details (10-fold Crossvalidation)
Number of instances
2000
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
0.733
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.73
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3219
Cross-validation details (10-fold Crossvalidation)
Recall
0.73
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.3
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2324
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.7746
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
941.5162[561.0294815668511012.8541257252805478.7078954039208898.36875100120691756.6205822745662]