Run
414208

Run 414208

Task 4596 (Supervised Classification) gina_agnostic Uploaded 07-05-2015 by Joaquin Vanschoren
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Flow

weka.END_ND_J48(3)Lin Dong, Eibe Frank, Stefan Kramer: Ensembles of Balanced Nested Dichotomies for Multi-class Problems. In: PKDD, 84-95, 2005. Eibe Frank, Stefan Kramer: Ensembles of nested dichotomies for multi-class problems. In: Twenty-first International Conference on Machine Learning, 2004.
weka.J48(28)_C0.25
weka.J48(28)_M2
weka.END_ND_J48(3)_S1
weka.END_ND_J48(3)_I10
weka.END_ND_J48(3)_Wweka.classifiers.meta.nestedDichotomies.ND
weka.ND_J48(3)_S1
weka.ND_J48(3)_Wweka.classifiers.trees.J48

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
0.8619
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
F measure
0.872
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
Kappa
0.7439
Cross-validation details (10 times 10-fold Crossvalidation)
KB relative information score
25431.1837
Cross-validation details (10 times 10-fold Crossvalidation)
Mean absolute error
0.1353
Cross-validation details (10 times 10-fold Crossvalidation)
Mean prior absolute error
0.4999
Cross-validation details (10 times 10-fold Crossvalidation)
Number of instances
34680
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.872
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
Predictive accuracy
0.872
Cross-validation details (10 times 10-fold Crossvalidation)
Prior entropy
0.9998
Cross-validation details (10 times 10-fold Crossvalidation)
Recall
0.872
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
Relative absolute error
0.2707
Cross-validation details (10 times 10-fold Crossvalidation)
Root mean prior squared error
0.4999
Cross-validation details (10 times 10-fold Crossvalidation)
Root mean squared error
0.3501
Cross-validation details (10 times 10-fold Crossvalidation)
Root relative squared error
0.7003
Cross-validation details (10 times 10-fold Crossvalidation)
SciMark benchmark
906.0884
UserCPU time millis
9230
Cross-validation details (10 times 10-fold Crossvalidation)
UserCPU time millis testing
50
Cross-validation details (10 times 10-fold Crossvalidation)
UserCPU time millis training
9180
Cross-validation details (10 times 10-fold Crossvalidation)