DEVELOPMENT... OpenML
Run
48635

Run 48635

Task 1701 (Learning Curve) anneal 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
0.9949 ± 0.0108
Per class
Build CPU time
0.0791
Build memory
1801326065.3333
F measure
0.9943 ± 0.0058
Per class
Kappa
0.986 ± 0.0205
KB relative information score
0.979 ± 0.0347
Mean absolute error
0.0024 ± 0.003
Mean prior absolute error
0.1343 ± 0.0013
Number of instances
898
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.9945 ± 0.0053
Per class
Predictive accuracy
0.9944 ± 0.0079
Prior entropy
1.1915 ± 0.026
Recall
0.9944 ± 0.0079
Per class
Relative absolute error
0.0175 ± 0.0221
Root mean prior squared error
0.2582 ± 0.0024
Root mean squared error
0.0419 ± 0.0325
Root relative squared error
0.1622 ± 0.1257
SciMark benchmark
1652.2022