DEVELOPMENT... OpenML
Run
159493

Run 159493

Task 3896 (Supervised Classification) ada_agnostic 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
0.8978
Per class
F measure
0.8463
Per class
Kappa
0.5754
KB relative information score
1943.0886
Mean absolute error
0.2058
Mean prior absolute error
0.3732
Number of instances
4562
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8459
Per class
Predictive accuracy
0.852
Prior entropy
0.8085
Recall
0.852
Per class
Relative absolute error
0.5514
Root mean prior squared error
0.4319
Root mean squared error
0.3241
Root relative squared error
0.7503
SciMark benchmark
911.0478
UserCPU time millis
1620
UserCPU time millis testing
10
UserCPU time millis training
1610

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