DEVELOPMENT... OpenML
Run
157716

Run 157716

Task 1748 (Learning Curve) tic-tac-toe Uploaded 12-02-2015 by Jason
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  • study_2 study_37 weka weka_3.7.12
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Flow

weka.HoeffdingTree(3)Geoff Hulten, Laurie Spencer, Pedro Domingos: Mining time-changing data streams. In: ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining, 97-106, 2001.
weka.HoeffdingTree(3)_L2
weka.HoeffdingTree(3)_S1
weka.HoeffdingTree(3)_E1.0E-7
weka.HoeffdingTree(3)_H0.05
weka.HoeffdingTree(3)_M0.01
weka.HoeffdingTree(3)_G200.0
weka.HoeffdingTree(3)_N0.0

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.

22 Evaluation measures

Area under ROC curve
0.7448 ± 0.0589
Per class
F measure
0.682 ± 0.0484
Per class
Kappa
0.2821 ± 0.1071
KB relative information score
0.1873 ± 0.057
Mean absolute error
0.3685 ± 0.0211
Mean prior absolute error
0.453 ± 0.0013
Number of instances
958
Per class
OS information
[Oracle Corporation, 1.7.0_75, amd64, Linux, 3.16.0-29-generic]
Precision
0.682 ± 0.0536
Per class
Predictive accuracy
0.6962 ± 0.0489
Prior entropy
0.931 ± 0.0039
Recall
0.6962 ± 0.0489
Per class
Relative absolute error
0.8133 ± 0.046
Root mean prior squared error
0.4759 ± 0.0014
Root mean squared error
0.43 ± 0.0222
Root relative squared error
0.9036 ± 0.0459
SciMark benchmark
646.4525
UserCPU time millis
10
UserCPU time millis training
10