DEVELOPMENT... OpenML
Run
160269

Run 160269

Task 3921 (Supervised Classification) jEdit_4.0_4.2 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
0.8127
Per class
F measure
0.7482
Per class
Kappa
0.4964
KB relative information score
113.1833
Mean absolute error
0.3034
Mean prior absolute error
0.4998
Number of instances
274
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7484
Per class
Predictive accuracy
0.7482
Prior entropy
0.9997
Recall
0.7482
Per class
Relative absolute error
0.607
Root mean prior squared error
0.4999
Root mean squared error
0.425
Root relative squared error
0.8502
SciMark benchmark
943.2817
UserCPU time millis
40
UserCPU time millis training
40