Run
413357

Run 413357

Task 3060 (Supervised Classification) squash-stored Uploaded 06-05-2015 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
0.6069
Per class
Cross-validation details (33% Holdout set)
F measure
0.5196
Per class
Cross-validation details (33% Holdout set)
Kappa
0.2
Cross-validation details (33% Holdout set)
KB relative information score
3.7017
Cross-validation details (33% Holdout set)
Mean absolute error
0.3579
Cross-validation details (33% Holdout set)
Mean prior absolute error
0.4164
Cross-validation details (33% Holdout set)
Number of instances
17
Per class
Cross-validation details (33% Holdout set)
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.5765
Per class
Cross-validation details (33% Holdout set)
Predictive accuracy
0.5294
Cross-validation details (33% Holdout set)
Prior entropy
1.4782
Cross-validation details (33% Holdout set)
Recall
0.5294
Per class
Cross-validation details (33% Holdout set)
Relative absolute error
0.8596
Cross-validation details (33% Holdout set)
Root mean prior squared error
0.4569
Cross-validation details (33% Holdout set)
Root mean squared error
0.4967
Cross-validation details (33% Holdout set)
Root relative squared error
1.087
Cross-validation details (33% Holdout set)
SciMark benchmark
926.5859
UserCPU time millis
10
UserCPU time millis training
10