Run
554272

Run 554272

Task 3812 (Supervised Classification) arsenic-female-bladder Uploaded 10-04-2016 by Martijn Post
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Flow

weka.JRip(5)William W. Cohen: Fast Effective Rule Induction. In: Twelfth International Conference on Machine Learning, 115-123, 1995.
weka.JRip(5)_F3
weka.JRip(5)_N2.0
weka.JRip(5)_O2
weka.JRip(5)_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
0.5364
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.811
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.1049
Cross-validation details (10-fold Crossvalidation)
KB relative information score
27.7335
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2313
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2462
Cross-validation details (10-fold Crossvalidation)
Number of instances
559
Per class
Cross-validation details (10-fold Crossvalidation)
OS information
[Oracle Corporation, 1.8.0_66, amd64, Windows 10, 10.0]
Precision
0.8273
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8605
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.5956
Cross-validation details (10-fold Crossvalidation)
Recall
0.8605
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9396
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3502
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3462
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9887
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
1834.908
UserCPU time millis
Cross-validation details (10-fold Crossvalidation)
UserCPU time millis training
Cross-validation details (10-fold Crossvalidation)