OpenML
698

Run 698

Task 89 (Learning Curve) page-blocks 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
0.806 ± 0.0258
Per class
F measure
0.9296 ± 0.0072
Per class
Kappa
0.6414 ± 0.041
KB relative information score
0.5224 ± 0.0476
Mean absolute error
0.0246 ± 0.0028
Mean prior absolute error
0.0762 ± 0.0003
Number of instances
54730
Per class
OS information
[ Sun Microsystems Inc., 1.6.0_30, amd64, Linux, 2.6.32-358.6.2.el6.x86_64 ]
Precision
0.9229 ± 0.0082
Per class
Predictive accuracy
0.9384 ± 0.0071
Prior entropy
0.6355 ± 0.0053
Recall
0.9384 ± 0.0071
Per class
Relative absolute error
0.3233 ± 0.0371
Root mean prior squared error
0.1948 ± 0.0007
Root mean squared error
0.1569 ± 0.009
Root relative squared error
0.8053 ± 0.0456
SciMark benchmark
699.131