DEVELOPMENT... OpenML
Run
157016

Run 157016

Task 3679 (Supervised Classification) chscase_vine2 Uploaded 11-02-2015 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)_I10
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
0.8627
Per class
F measure
0.7907
Per class
Kappa
0.5768
KB relative information score
193.1368
Mean absolute error
0.3074
Mean prior absolute error
0.4956
Number of instances
468
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7949
Per class
Predictive accuracy
0.7927
Prior entropy
0.9937
Recall
0.7927
Per class
Relative absolute error
0.6202
Root mean prior squared error
0.4978
Root mean squared error
0.3858
Root relative squared error
0.775
SciMark benchmark
929.566
UserCPU time millis
10
UserCPU time millis training
10