DEVELOPMENT... OpenML
Run
156837

Run 156837

Task 3505 (Supervised Classification) codrna 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
0.9376
Per class
F measure
0.8856
Per class
Kappa
0.7394
KB relative information score
261677.3857
Mean absolute error
0.2253
Mean prior absolute error
0.4444
Number of instances
488565
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8864
Per class
Predictive accuracy
0.8873
Prior entropy
0.9183
Recall
0.8873
Per class
Relative absolute error
0.5069
Root mean prior squared error
0.4714
Root mean squared error
0.3028
Root relative squared error
0.6424
SciMark benchmark
940.2922
UserCPU time millis
47920
UserCPU time millis testing
580
UserCPU time millis training
47340