DEVELOPMENT... OpenML
Run
157335

Run 157335

Task 3535 (Supervised Classification) tr41.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
0.9995
Per class
F measure
0.9733
Per class
Kappa
0.9696
KB relative information score
843.1726
Mean absolute error
0.0075
Mean prior absolute error
0.1652
Number of instances
878
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9753
Per class
Predictive accuracy
0.9749
Prior entropy
2.8041
Recall
0.9749
Per class
Relative absolute error
0.0457
Root mean prior squared error
0.2872
Root mean squared error
0.0581
Root relative squared error
0.2022
SciMark benchmark
940.2922
UserCPU time millis
587390
UserCPU time millis testing
10
UserCPU time millis training
587380