DEVELOPMENT... OpenML
Run
160908

Run 160908

Task 3594 (Supervised Classification) analcatdata_supreme Uploaded 15-02-2015 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)_I160
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
0.9981
Per class
F measure
0.9923
Per class
Kappa
0.9789
KB relative information score
3935.1734
Mean absolute error
0.0102
Mean prior absolute error
0.3645
Number of instances
4052
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9923
Per class
Predictive accuracy
0.9923
Prior entropy
0.7946
Recall
0.9923
Per class
Relative absolute error
0.0281
Root mean prior squared error
0.4269
Root mean squared error
0.0756
Root relative squared error
0.1771
SciMark benchmark
936.6206
UserCPU time millis
780
UserCPU time millis training
780