DEVELOPMENT... OpenML
Run
157404

Run 157404

Task 7307 (Supervised Classification) eating 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
0.8449
Per class
F measure
0.4986
Per class
Kappa
0.417
KB relative information score
418.5632
Mean absolute error
0.1637
Mean prior absolute error
0.2448
Number of instances
945
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.4978
Per class
Predictive accuracy
0.5005
Prior entropy
2.8053
Recall
0.5005
Per class
Relative absolute error
0.6688
Root mean prior squared error
0.3498
Root mean squared error
0.3006
Root relative squared error
0.8592
SciMark benchmark
929.566
UserCPU time millis
126800
UserCPU time millis testing
10
UserCPU time millis training
126790