DEVELOPMENT... OpenML
Run
157234

Run 157234

Task 3895 (Supervised Classification) gina_prior 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
0.8984
Per class
F measure
0.8252
Per class
Kappa
0.6504
KB relative information score
1823.6263
Mean absolute error
0.2517
Mean prior absolute error
0.4999
Number of instances
3468
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8253
Per class
Predictive accuracy
0.8253
Prior entropy
0.9998
Recall
0.8253
Per class
Relative absolute error
0.5036
Root mean prior squared error
0.4999
Root mean squared error
0.3553
Root relative squared error
0.7106
SciMark benchmark
943.2817
UserCPU time millis
5310
UserCPU time millis testing
10
UserCPU time millis training
5300