Run
52

Run 52

Task 72 (Learning Curve) breast-cancer Uploaded 06-04-2014 by Jan van Rijn
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Flow

weka.JRip(1)William W. Cohen: Fast Effective Rule Induction. In: Twelfth International Conference on Machine Learning, 115-123, 1995.
weka.JRip(1)_F3
weka.JRip(1)_N2.0
weka.JRip(1)_O2
weka.JRip(1)_S1

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

19 Evaluation measures

Area under ROC curve
0.6025 ± 0.0844
Per class
F measure
0.7001 ± 0.0758
Per class
Kappa
0.2522 ± 0.1803
KB relative information score
0.108 ± 0.1046
Mean absolute error
0.3748 ± 0.034
Mean prior absolute error
0.4183 ± 0.0065
Number of instances
2860
Per class
OS information
[ Oracle Corporation, 1.7.0_51, amd64, Linux, 3.7.10-1.28-desktop ]
Precision
0.7008 ± 0.0962
Per class
Predictive accuracy
0.7248 ± 0.071
Prior entropy
0.8779 ± 0.0199
Recall
0.7248 ± 0.071
Per class
Relative absolute error
0.896 ± 0.0777
Root mean prior squared error
0.457 ± 0.0071
Root mean squared error
0.4479 ± 0.0434
Root relative squared error
0.9799 ± 0.0907
SciMark benchmark
1950.8387