DEVELOPMENT... OpenML
Run
60052

Run 60052

Task 1742 (Learning Curve) spambase Uploaded 16-11-2014 by Jason
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  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
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Flow

weka.MultiBoostAB_JRip(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.JRip(2)_F3
weka.JRip(2)_N2.0
weka.JRip(2)_O2
weka.JRip(2)_S1
weka.MultiBoostAB_JRip(2)_C3
weka.MultiBoostAB_JRip(2)_P100
weka.MultiBoostAB_JRip(2)_S1
weka.MultiBoostAB_JRip(2)_I10
weka.MultiBoostAB_JRip(2)_Wweka.classifiers.rules.JRip

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
0.9759 ± 0.0055
Per class
Build CPU time
2.5539
Build memory
1772746880.6857
F measure
0.9436 ± 0.0121
Per class
Kappa
0.8819 ± 0.0254
KB relative information score
0.8793 ± 0.0251
Mean absolute error
0.0567 ± 0.0116
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
0.9436 ± 0.0122
Per class
Predictive accuracy
0.9437 ± 0.0121
Prior entropy
0.9674 ± 0.0006
Recall
0.9437 ± 0.0121
Per class
Relative absolute error
0.1188 ± 0.0244
Root mean prior squared error
0.4886 ± 0.0002
Root mean squared error
0.2299 ± 0.0249
Root relative squared error
0.4706 ± 0.051
SciMark benchmark
1091.0812