Run
148929

Run 148929

Task 3837 (Supervised Classification) hayes-roth Uploaded 06-02-2015 by Joaquin Vanschoren
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Flow

weka.Decorate(1)P. Melville, R. J. Mooney: Constructing Diverse Classifier Ensembles Using Artificial Training Examples. In: Eighteenth International Joint Conference on Artificial Intelligence, 505-510, 2003. P. Melville, R. J. Mooney (2004). Creating Diversity in Ensembles Using Artificial Data. Information Fusion: Special Issue on Diversity in Multiclassifier Systems..
weka.Decorate(1)_E15
weka.Decorate(1)_R1.0
weka.Decorate(1)_S1
weka.Decorate(1)_I50

Result files

xml
Description

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

model
Model readable

A human-readable description of the model that was built.

model
Model serialized

A serialized description of the model that can be read by the tool that generated it.

arff
Predictions

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

22 Evaluation measures

Area under ROC curve
0.8948
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.785
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.5427
Cross-validation details (10-fold Crossvalidation)
KB relative information score
14.9337
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.4339
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4746
Cross-validation details (10-fold Crossvalidation)
Number of instances
132
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
0.7857
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7879
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9635
Cross-validation details (10-fold Crossvalidation)
Recall
0.7879
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9144
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4869
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4401
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9038
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
947.9494
UserCPU time millis
50
Cross-validation details (10-fold Crossvalidation)
UserCPU time millis training
50
Cross-validation details (10-fold Crossvalidation)