DEVELOPMENT... OpenML
Run
159015

Run 159015

Task 1752 (Learning Curve) vehicle 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
0.8679 ± 0.0399
Per class
F measure
0.6672 ± 0.064
Per class
Kappa
0.5725 ± 0.0812
KB relative information score
0.5738 ± 0.0776
Mean absolute error
0.1931 ± 0.031
Mean prior absolute error
0.3748 ± 0
Number of instances
846
Per class
OS information
[Oracle Corporation, 1.7.0_75, amd64, Linux, 3.16.0-29-generic]
Precision
0.6647 ± 0.0677
Per class
Predictive accuracy
0.6797 ± 0.0606
Prior entropy
1.9991 ± 0.0005
Recall
0.6797 ± 0.0606
Per class
Relative absolute error
0.5152 ± 0.0829
Root mean prior squared error
0.4329 ± 0
Root mean squared error
0.331 ± 0.0322
Root relative squared error
0.7647 ± 0.0744
SciMark benchmark
642.8724
UserCPU time millis
240
UserCPU time millis training
240