OpenML
47636

Run 47636

Task 88 (Learning Curve) credit-approval Uploaded 05-11-2014 by Jan van Rijn
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Flow

weka.OneR(3)R.C. Holte (1993). Very simple classification rules perform well on most commonly used datasets. Machine Learning. 11:63-91.
weka.OneR(3)_B6

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.

21 Evaluation measures

Area under ROC curve
0.862 ± 0.0334
Per class
Build CPU time
0.0005
Build memory
3187284860.07
F measure
0.8554 ± 0.0349
Per class
Kappa
0.7116 ± 0.068
KB relative information score
0.705 ± 0.0708
Mean absolute error
0.1449 ± 0.0348
Mean prior absolute error
0.494 ± 0.0007
Number of instances
6900
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.8663 ± 0.0318
Per class
Predictive accuracy
0.8551 ± 0.0348
Prior entropy
0.9912 ± 0.0021
Recall
0.8551 ± 0.0348
Per class
Relative absolute error
0.2934 ± 0.0704
Root mean prior squared error
0.497 ± 0.0007
Root mean squared error
0.3807 ± 0.0455
Root relative squared error
0.766 ± 0.0916
SciMark benchmark
1445.6628