DEVELOPMENT... OpenML
Run
160834

Run 160834

Task 3521 (Supervised Classification) oh15.wc 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
0.9799
Per class
F measure
0.8565
Per class
Kappa
0.837
KB relative information score
769.9067
Mean absolute error
0.0304
Mean prior absolute error
0.1768
Number of instances
913
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.862
Per class
Predictive accuracy
0.8565
Prior entropy
3.2121
Recall
0.8565
Per class
Relative absolute error
0.1722
Root mean prior squared error
0.2973
Root mean squared error
0.156
Root relative squared error
0.5247
SciMark benchmark
932.3943
UserCPU time millis
3034730
UserCPU time millis training
3034730