DEVELOPMENT... OpenML
Run
156626

Run 156626

Task 49 (Supervised Classification) tic-tac-toe Uploaded 11-02-2015 by Felicia West
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Flow

weka.LogitBoost_DecisionStump(2)J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
weka.LogitBoost_DecisionStump(2)_E1
weka.LogitBoost_DecisionStump(2)_H1.0
weka.LogitBoost_DecisionStump(2)_I10
weka.LogitBoost_DecisionStump(2)_L-1.7976931348623157E308
weka.LogitBoost_DecisionStump(2)_O1
weka.LogitBoost_DecisionStump(2)_P100
weka.LogitBoost_DecisionStump(2)_S1
weka.LogitBoost_DecisionStump(2)_Wweka.classifiers.trees.DecisionStump
weka.LogitBoost_DecisionStump(2)_Z3.0

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
0.7997
Per class
F measure
0.7085
Per class
Kappa
0.3413
KB relative information score
220.1053
Mean absolute error
0.3526
Mean prior absolute error
0.453
Number of instances
958
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7125
Per class
Predictive accuracy
0.7234
Prior entropy
0.9312
Recall
0.7234
Per class
Relative absolute error
0.7784
Root mean prior squared error
0.4759
Root mean squared error
0.4122
Root relative squared error
0.8662
SciMark benchmark
943.2817
UserCPU time millis
10
UserCPU time millis training
10