DEVELOPMENT... OpenML
Run
157137

Run 157137

Task 3799 (Supervised Classification) fri_c3_500_10 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
0.9055
Per class
F measure
0.8161
Per class
Kappa
0.6294
KB relative information score
249.3478
Mean absolute error
0.2639
Mean prior absolute error
0.4961
Number of instances
500
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8162
Per class
Predictive accuracy
0.816
Prior entropy
0.9945
Recall
0.816
Per class
Relative absolute error
0.5319
Root mean prior squared error
0.4981
Root mean squared error
0.3528
Root relative squared error
0.7083
SciMark benchmark
929.566
UserCPU time millis
10
UserCPU time millis training
10

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