DEVELOPMENT... OpenML
Run
60053

Run 60053

Task 1748 (Learning Curve) tic-tac-toe 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
0.9965 ± 0.0097
Per class
Build CPU time
0.0696
Build memory
2456656102.6667
F measure
0.9885 ± 0.0092
Per class
Kappa
0.9745 ± 0.0205
KB relative information score
0.9753 ± 0.0204
Mean absolute error
0.0108 ± 0.0089
Mean prior absolute error
0.453 ± 0.0013
Number of instances
958
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.9886 ± 0.009
Per class
Predictive accuracy
0.9885 ± 0.0092
Prior entropy
0.931 ± 0.0039
Recall
0.9885 ± 0.0092
Per class
Relative absolute error
0.0239 ± 0.0196
Root mean prior squared error
0.4759 ± 0.0014
Root mean squared error
0.0965 ± 0.0598
Root relative squared error
0.2029 ± 0.1258
SciMark benchmark
1091.0812