DEVELOPMENT... OpenML
Run
159163

Run 159163

Task 3521 (Supervised Classification) oh15.wc 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
0.9811
Per class
F measure
0.8434
Per class
Kappa
0.822
KB relative information score
749.791
Mean absolute error
0.0375
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
0.8486
Per class
Predictive accuracy
0.8434
Prior entropy
3.2121
Recall
0.8434
Per class
Relative absolute error
0.2119
Root mean prior squared error
0.2973
Root mean squared error
0.1528
Root relative squared error
0.5142
SciMark benchmark
933.1776
UserCPU time millis
809760
UserCPU time millis testing
10
UserCPU time millis training
809750