DEVELOPMENT... OpenML
Run
160263

Run 160263

Task 3915 (Supervised Classification) kc3 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)_I80
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
0.756
Per class
F measure
0.8794
Per class
Kappa
0.2299
KB relative information score
-58.7197
Mean absolute error
0.1375
Mean prior absolute error
0.1716
Number of instances
458
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8715
Per class
Predictive accuracy
0.8908
Prior entropy
0.4551
Recall
0.8908
Per class
Relative absolute error
0.8012
Root mean prior squared error
0.2917
Root mean squared error
0.3034
Root relative squared error
1.0403
SciMark benchmark
943.2817
UserCPU time millis
210
UserCPU time millis training
210