DEVELOPMENT... OpenML
Run
159010

Run 159010

Task 1740 (Learning Curve) soybean Uploaded 12-02-2015 by Jason
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  • study_2 study_37 weka weka_3.7.12
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Flow

weka.JRip(4)William W. Cohen: Fast Effective Rule Induction. In: Twelfth International Conference on Machine Learning, 115-123, 1995.
weka.JRip(4)_F3
weka.JRip(4)_N2.0
weka.JRip(4)_O2
weka.JRip(4)_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
0.9823 ± 0.0139
Per class
F measure
0.9231 ± 0.0383
Per class
Kappa
0.9165 ± 0.0409
KB relative information score
0.9276 ± 0.0297
Mean absolute error
0.0103 ± 0.0033
Mean prior absolute error
0.0961 ± 0.0001
Number of instances
683
Per class
OS information
[Oracle Corporation, 1.7.0_75, amd64, Linux, 3.16.0-29-generic]
Precision
0.9259 ± 0.0325
Per class
Predictive accuracy
0.9239 ± 0.0373
Prior entropy
3.8358 ± 0.0227
Recall
0.9239 ± 0.0373
Per class
Relative absolute error
0.1071 ± 0.0341
Root mean prior squared error
0.2191 ± 0.0002
Root mean squared error
0.0817 ± 0.0205
Root relative squared error
0.3728 ± 0.0936
SciMark benchmark
646.4525
UserCPU time millis
100
UserCPU time millis training
100