DEVELOPMENT... OpenML
Run
156861

Run 156861

Task 3521 (Supervised Classification) oh15.wc 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
0.9765
Per class
F measure
0.8314
Per class
Kappa
0.8084
KB relative information score
708.9581
Mean absolute error
0.0522
Mean prior absolute error
0.1768
Number of instances
913
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8353
Per class
Predictive accuracy
0.8313
Prior entropy
3.2121
Recall
0.8313
Per class
Relative absolute error
0.2954
Root mean prior squared error
0.2973
Root mean squared error
0.1561
Root relative squared error
0.525
SciMark benchmark
943.2817
UserCPU time millis
200590
UserCPU time millis training
200590