DEVELOPMENT... OpenML
Run
159218

Run 159218

Task 3576 (Supervised Classification) sleuth_ex2015 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
0.7133
Per class
F measure
0.6663
Per class
Kappa
0.3333
KB relative information score
19.3665
Mean absolute error
0.343
Mean prior absolute error
0.5
Number of instances
60
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.6674
Per class
Predictive accuracy
0.6667
Prior entropy
1
Recall
0.6667
Per class
Relative absolute error
0.686
Root mean prior squared error
0.5
Root mean squared error
0.5077
Root relative squared error
1.0153
SciMark benchmark
924.6116
UserCPU time millis
10
UserCPU time millis training
10