DEVELOPMENT... OpenML
Run
159907

Run 159907

Task 3521 (Supervised Classification) oh15.wc Uploaded 13-02-2015 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)_I80
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
0.9815
Per class
F measure
0.8458
Per class
Kappa
0.8245
KB relative information score
763.3317
Mean absolute error
0.0328
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
0.8514
Per class
Predictive accuracy
0.8456
Prior entropy
3.2121
Recall
0.8456
Per class
Relative absolute error
0.1858
Root mean prior squared error
0.2973
Root mean squared error
0.1537
Root relative squared error
0.5172
SciMark benchmark
897.6255
UserCPU time millis
1588050
UserCPU time millis training
1588050