Run
222495

Run 222495

Task 3750 (Supervised Classification) mbagrade Uploaded 01-03-2015 by Joaquin Vanschoren
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Flow

weka.JRip(4)William W. Cohen: Fast Effective Rule Induction. In: Twelfth International Conference on Machine Learning, 115-123, 1995.
weka.JRip(4)_F3
weka.JRip(4)_N2.0
weka.JRip(4)_O2
weka.JRip(4)_S1

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
0.5938
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.6305
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.2675
Cross-validation details (10-fold Crossvalidation)
KB relative information score
7.2018
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.451
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4988
Cross-validation details (10-fold Crossvalidation)
Number of instances
61
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
0.6448
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.6393
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9984
Cross-validation details (10-fold Crossvalidation)
Recall
0.6393
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.904
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4994
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4989
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9991
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
912.7324
UserCPU time millis training