Run
14926

Run 14926

Task 59 (Supervised Classification) iris Uploaded 03-06-2014 by Joaquin Vanschoren
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Flow

weka.MultiBoostAB_REPTree(1)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.MultiBoostAB_REPTree(1)_C3
weka.MultiBoostAB_REPTree(1)_I160
weka.MultiBoostAB_REPTree(1)_P100
weka.MultiBoostAB_REPTree(1)_S1
weka.MultiBoostAB_REPTree(1)_Wweka.classifiers.trees.REPTree
weka.REPTree(1)_I0.0
weka.REPTree(1)_L-1
weka.REPTree(1)_M2
weka.REPTree(1)_N3
weka.REPTree(1)_S1
weka.REPTree(1)_V0.001

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
0.9791
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.94
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.91
Cross-validation details (10-fold Crossvalidation)
KB relative information score
139.0526
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0361
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4444
Cross-validation details (10-fold Crossvalidation)
Number of instances
150
Per class
Cross-validation details (10-fold Crossvalidation)
OS information
[Oracle Corporation, 1.7.0_04, x86_64, Mac OS X, 10.9.3]
Precision
0.9401
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.94
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.585
Cross-validation details (10-fold Crossvalidation)
Recall
0.94
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.0813
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4714
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1739
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.3688
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
1273.5018[907.98575561494491186.5485972905478545.18496503926621122.19168278084232605.5980189114316]