DEVELOPMENT... OpenML
Run
48656

Run 48656

Task 1748 (Learning Curve) tic-tac-toe 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
0.9994 ± 0.0003
Per class
Build CPU time
0.0961
Build memory
1481768464.4445
F measure
0.9927 ± 0.0099
Per class
Kappa
0.9838 ± 0.0221
KB relative information score
0.9824 ± 0.0207
Mean absolute error
0.0079 ± 0.0088
Mean prior absolute error
0.453 ± 0.0013
Number of instances
958
Per class
OS information
[Oracle Corporation, 1.7.0_65, amd64, Linux, 3.5.0-54-generic]
Precision
0.9927 ± 0.0099
Per class
Predictive accuracy
0.9927 ± 0.0099
Prior entropy
0.931 ± 0.0039
Recall
0.9927 ± 0.0099
Per class
Relative absolute error
0.0174 ± 0.0196
Root mean prior squared error
0.4759 ± 0.0014
Root mean squared error
0.0767 ± 0.0555
Root relative squared error
0.1613 ± 0.1169
SciMark benchmark
1794.5417