Run
417563

Run 417563

Task 4229 (Supervised Classification) fbis.wc Uploaded 07-05-2015 by Joaquin Vanschoren
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


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
0.9813
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
F measure
0.8236
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
Kappa
0.8077
Cross-validation details (10 times 10-fold Crossvalidation)
KB relative information score
19275.7104
Cross-validation details (10 times 10-fold Crossvalidation)
Mean absolute error
0.0365
Cross-validation details (10 times 10-fold Crossvalidation)
Mean prior absolute error
0.1047
Cross-validation details (10 times 10-fold Crossvalidation)
Number of instances
24630
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
0.8241
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
Predictive accuracy
0.8301
Cross-validation details (10 times 10-fold Crossvalidation)
Prior entropy
3.5848
Cross-validation details (10 times 10-fold Crossvalidation)
Recall
0.8301
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
Relative absolute error
0.3487
Cross-validation details (10 times 10-fold Crossvalidation)
Root mean prior squared error
0.2288
Cross-validation details (10 times 10-fold Crossvalidation)
Root mean squared error
0.1251
Cross-validation details (10 times 10-fold Crossvalidation)
Root relative squared error
0.5469
Cross-validation details (10 times 10-fold Crossvalidation)
SciMark benchmark
926.5859
UserCPU time millis
1092160
Cross-validation details (10 times 10-fold Crossvalidation)
UserCPU time millis testing
1060
Cross-validation details (10 times 10-fold Crossvalidation)
UserCPU time millis training
1091100
Cross-validation details (10 times 10-fold Crossvalidation)