Run
53881

Run 53881

Task 1748 (Learning Curve) tic-tac-toe Uploaded 08-11-2014 by Jan van Rijn
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  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
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Flow

weka.RealAdaBoost_Logistic(1)J. Friedman, T. Hastie, R. Tibshirani (2000). Additive Logistic Regression: a Statistical View of Boosting. Annals of Statistics. 95(2):337-407.
weka.Logistic(2)_M-1
weka.Logistic(2)_R1.0E-8
weka.RealAdaBoost_Logistic(1)_P100
weka.RealAdaBoost_Logistic(1)_H1.0
weka.RealAdaBoost_Logistic(1)_S1
weka.RealAdaBoost_Logistic(1)_I10
weka.RealAdaBoost_Logistic(1)_Wweka.classifiers.functions.Logistic

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
0.9964 ± 0.0022
Per class
Build CPU time
0.0886
Build memory
3115903460.9778
F measure
0.9822 ± 0.0133
Per class
Kappa
0.9604 ± 0.0298
KB relative information score
0.936 ± 0.0267
Mean absolute error
0.0297 ± 0.0113
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
0.9826 ± 0.0124
Per class
Predictive accuracy
0.9823 ± 0.0131
Prior entropy
0.931 ± 0.0039
Recall
0.9823 ± 0.0131
Per class
Relative absolute error
0.0655 ± 0.0248
Root mean prior squared error
0.4759 ± 0.0014
Root mean squared error
0.13 ± 0.0403
Root relative squared error
0.2732 ± 0.0846
SciMark benchmark
1624.8488