DEVELOPMENT... OpenML
Run
48713

Run 48713

Task 1742 (Learning Curve) spambase 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
0.9574 ± 0.0082
Per class
Build CPU time
0.167
Build memory
4105910852.9714
F measure
0.9364 ± 0.0109
Per class
Kappa
0.8665 ± 0.0228
KB relative information score
0.8426 ± 0.0168
Mean absolute error
0.0769 ± 0.0078
Mean prior absolute error
0.4776 ± 0.0002
Number of instances
4601
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.9364 ± 0.0111
Per class
Predictive accuracy
0.9365 ± 0.0109
Prior entropy
0.9674 ± 0.0006
Recall
0.9365 ± 0.0109
Per class
Relative absolute error
0.1611 ± 0.0164
Root mean prior squared error
0.4886 ± 0.0002
Root mean squared error
0.2373 ± 0.0188
Root relative squared error
0.4857 ± 0.0386
SciMark benchmark
1729.8248