DEVELOPMENT... OpenML
Run
160392

Run 160392

Task 2142 (Supervised Classification) BNG(breast-w) Uploaded 13-02-2015 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
0.9988
Per class
F measure
0.9859
Per class
Kappa
0.9688
KB relative information score
37576.8929
Mean absolute error
0.0216
Mean prior absolute error
0.4514
Number of instances
39366
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9859
Per class
Predictive accuracy
0.9859
Prior entropy
0.9287
Recall
0.9859
Per class
Relative absolute error
0.0479
Root mean prior squared error
0.4751
Root mean squared error
0.1042
Root relative squared error
0.2194
SciMark benchmark
911.0478
UserCPU time millis
24790
UserCPU time millis testing
30
UserCPU time millis training
24760