Run
808

Run 808

Task 72 (Learning Curve) breast-cancer Uploaded 08-04-2014 by Jan van Rijn
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Flow

weka.OneR(1)R.C. Holte (1993). Very simple classification rules perform well on most commonly used datasets. Machine Learning. 11:63-91.
weka.OneR(1)_B6

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
0.5316 ± 0.0636
Per class
F measure
0.6297 ± 0.0613
Per class
Kappa
0.0741 ± 0.1443
KB relative information score
0.152 ± 0.1498
Mean absolute error
0.3301 ± 0.0601
Mean prior absolute error
0.4183 ± 0.0065
Number of instances
2860
Per class
OS information
[ Sun Microsystems Inc., 1.6.0_30, amd64, Linux, 2.6.32-358.6.2.el6.x86_64 ]
Precision
0.62 ± 0.101
Per class
Predictive accuracy
0.6699 ± 0.0601
Prior entropy
0.8779 ± 0.0199
Recall
0.6699 ± 0.0601
Per class
Relative absolute error
0.789 ± 0.1405
Root mean prior squared error
0.457 ± 0.0071
Root mean squared error
0.5745 ± 0.0522
Root relative squared error
1.2571 ± 0.11
SciMark benchmark
919.1682