DEVELOPMENT... OpenML
Run
48705

Run 48705

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.PART(2)Eibe Frank, Ian H. Witten: Generating Accurate Rule Sets Without Global Optimization. In: Fifteenth International Conference on Machine Learning, 144-151, 1998.
weka.PART(2)_C0.25
weka.PART(2)_M2
weka.PART(2)_Q1

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
0.9766 ± 0.0324
Per class
Build CPU time
0.0016
Build memory
611325036.4444
F measure
0.9465 ± 0.0401
Per class
Kappa
0.8815 ± 0.0884
KB relative information score
0.8577 ± 0.1011
Mean absolute error
0.0649 ± 0.0458
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
0.9466 ± 0.0404
Per class
Predictive accuracy
0.9468 ± 0.0398
Prior entropy
0.931 ± 0.0039
Recall
0.9468 ± 0.0398
Per class
Relative absolute error
0.1433 ± 0.1007
Root mean prior squared error
0.4759 ± 0.0014
Root mean squared error
0.2181 ± 0.0716
Root relative squared error
0.4583 ± 0.1496
SciMark benchmark
1193.7396