Run
413960

Run 413960

Task 4350 (Supervised Classification) fri_c1_500_25 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
0.8068
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
F measure
0.8158
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
Kappa
0.63
Cross-validation details (10 times 10-fold Crossvalidation)
KB relative information score
3084.7809
Cross-validation details (10 times 10-fold Crossvalidation)
Mean absolute error
0.1926
Cross-validation details (10 times 10-fold Crossvalidation)
Mean prior absolute error
0.4977
Cross-validation details (10 times 10-fold Crossvalidation)
Number of instances
5000
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
0.8158
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
Predictive accuracy
0.8158
Cross-validation details (10 times 10-fold Crossvalidation)
Prior entropy
0.9967
Cross-validation details (10 times 10-fold Crossvalidation)
Recall
0.8158
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
Relative absolute error
0.3871
Cross-validation details (10 times 10-fold Crossvalidation)
Root mean prior squared error
0.4988
Cross-validation details (10 times 10-fold Crossvalidation)
Root mean squared error
0.4168
Cross-validation details (10 times 10-fold Crossvalidation)
Root relative squared error
0.8355
Cross-validation details (10 times 10-fold Crossvalidation)
SciMark benchmark
922.8232
UserCPU time millis
20
Cross-validation details (10 times 10-fold Crossvalidation)
UserCPU time millis testing
10
Cross-validation details (10 times 10-fold Crossvalidation)
UserCPU time millis training
10
Cross-validation details (10 times 10-fold Crossvalidation)