DEVELOPMENT... OpenML
Run
48643

Run 48643

Task 1722 (Learning Curve) cmc 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.AdaBoostM1_JRip(2)Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
weka.AdaBoostM1_JRip(2)_I10
weka.AdaBoostM1_JRip(2)_P100
weka.AdaBoostM1_JRip(2)_S1
weka.AdaBoostM1_JRip(2)_Wweka.classifiers.rules.JRip
weka.JRip(2)_F3
weka.JRip(2)_N2.0
weka.JRip(2)_O2
weka.JRip(2)_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.

21 Evaluation measures

Area under ROC curve
0.6492 ± 0.0269
Per class
Build CPU time
0.0219
Build memory
889156477.76
F measure
0.5206 ± 0.0534
Per class
Kappa
0.2564 ± 0.079
KB relative information score
0.078 ± 0.0587
Mean absolute error
0.4207 ± 0.0213
Mean prior absolute error
0.4308 ± 0.0004
Number of instances
1473
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.5331 ± 0.0575
Per class
Predictive accuracy
0.5363 ± 0.0487
Prior entropy
1.539 ± 0.0029
Recall
0.5363 ± 0.0487
Per class
Relative absolute error
0.9766 ± 0.0491
Root mean prior squared error
0.4641 ± 0.0005
Root mean squared error
0.4541 ± 0.0115
Root relative squared error
0.9785 ± 0.0244
SciMark benchmark
1627.4256