DEVELOPMENT... OpenML
Run
159504

Run 159504

Task 3907 (Supervised Classification) mc1 Uploaded 12-02-2015 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)_I40
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
0.9416
Per class
F measure
0.993
Per class
Kappa
0.4155
KB relative information score
-24031.1995
Mean absolute error
0.0103
Mean prior absolute error
0.0144
Number of instances
9466
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9936
Per class
Predictive accuracy
0.9944
Prior entropy
0.0622
Recall
0.9944
Per class
Relative absolute error
0.7193
Root mean prior squared error
0.0845
Root mean squared error
0.0729
Root relative squared error
0.8629
SciMark benchmark
911.0478
UserCPU time millis
3200
UserCPU time millis testing
10
UserCPU time millis training
3190