DEVELOPMENT... OpenML
Run
48675

Run 48675

Task 2102 (Learning Curve) eucalyptus Uploaded 05-11-2014 by Jason
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  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
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Flow

weka.PART(2)Eibe Frank, Ian H. Witten: Generating Accurate Rule Sets Without Global Optimization. In: Fifteenth International Conference on Machine Learning, 144-151, 1998.
weka.PART(2)_C0.25
weka.PART(2)_M2
weka.PART(2)_Q1

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
0.8105 ± 0.0375
Per class
Build CPU time
0.0307
Build memory
2086850408.4
F measure
0.5928 ± 0.047
Per class
Kappa
0.4795 ± 0.0587
KB relative information score
0.5155 ± 0.0525
Mean absolute error
0.1747 ± 0.0158
Mean prior absolute error
0.3132 ± 0.0002
Number of instances
736
Per class
OS information
[Oracle Corporation, 1.7.0_65, amd64, Linux, 3.5.0-54-generic]
Precision
0.5943 ± 0.0488
Per class
Predictive accuracy
0.5924 ± 0.0452
Prior entropy
2.2621 ± 0.0043
Recall
0.5924 ± 0.0452
Per class
Relative absolute error
0.5577 ± 0.0503
Root mean prior squared error
0.3957 ± 0.0003
Root mean squared error
0.3576 ± 0.024
Root relative squared error
0.9036 ± 0.0604
SciMark benchmark
1970.0822