DEVELOPMENT... OpenML
Run
159012

Run 159012

Task 1742 (Learning Curve) spambase 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
0.9356 ± 0.0106
Per class
F measure
0.9282 ± 0.0102
Per class
Kappa
0.8494 ± 0.0216
KB relative information score
0.7843 ± 0.022
Mean absolute error
0.1121 ± 0.0104
Mean prior absolute error
0.4776 ± 0.0002
Number of instances
4601
Per class
OS information
[Oracle Corporation, 1.7.0_75, amd64, Linux, 3.16.0-29-generic]
Precision
0.9281 ± 0.0102
Per class
Predictive accuracy
0.9283 ± 0.0101
Prior entropy
0.9674 ± 0.0006
Recall
0.9283 ± 0.0101
Per class
Relative absolute error
0.2348 ± 0.0218
Root mean prior squared error
0.4886 ± 0.0002
Root mean squared error
0.2547 ± 0.0179
Root relative squared error
0.5212 ± 0.0367
SciMark benchmark
646.4525
UserCPU time millis
2640
UserCPU time millis training
2640