OpenML
18159

Run 18159

Task 31 (Supervised Classification) credit-g Uploaded 10-06-2014 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)_I40
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
0.6271
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.6727
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.2179
Cross-validation details (10-fold Crossvalidation)
KB relative information score
162.4164
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3277
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4202
Cross-validation details (10-fold Crossvalidation)
Number of instances
1000
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
0.6715
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.674
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.8818
Cross-validation details (10-fold Crossvalidation)
Recall
0.674
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.7799
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4583
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.5568
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.2151
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
916.8154[565.3940416310953864.4930142903995484.10363182779514914.03067367712611756.0556588021248]