DEVELOPMENT... OpenML
Run
160245

Run 160245

Task 3899 (Supervised Classification) mozilla4 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
0.9655
Per class
F measure
0.9405
Per class
Kappa
0.8629
KB relative information score
12387.0649
Mean absolute error
0.096
Mean prior absolute error
0.4412
Number of instances
15545
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9451
Per class
Predictive accuracy
0.9419
Prior entropy
0.9135
Recall
0.9419
Per class
Relative absolute error
0.2176
Root mean prior squared error
0.4697
Root mean squared error
0.2179
Root relative squared error
0.4638
SciMark benchmark
943.2817
UserCPU time millis
1640
UserCPU time millis testing
10
UserCPU time millis training
1630