Run
159092

Run 159092

Task 1764 (Learning Curve) electricity Uploaded 12-02-2015 by Jan van Rijn
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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
0.8714 ± 0.0114
Per class
F measure
0.8548 ± 0.0112
Per class
Kappa
0.702 ± 0.0223
KB relative information score
0.5641 ± 0.035
Mean absolute error
0.2307 ± 0.0179
Mean prior absolute error
0.4886 ± 0
Number of instances
45312
Per class
OS information
[Oracle Corporation, 1.7.0_75, amd64, Linux, 3.16.0-29-generic]
Precision
0.8551 ± 0.0115
Per class
Predictive accuracy
0.8554 ± 0.0116
Prior entropy
0.9835 ± 0
Recall
0.8554 ± 0.0116
Per class
Relative absolute error
0.4721 ± 0.0366
Root mean prior squared error
0.4943 ± 0
Root mean squared error
0.3451 ± 0.0116
Root relative squared error
0.6982 ± 0.0235
SciMark benchmark
642.8724
UserCPU time millis
23820
UserCPU time millis testing
100
UserCPU time millis training
23720