DEVELOPMENT... OpenML
Run
88230

Run 88230

Task 3665 (Supervised Classification) pyrim Uploaded 03-12-2014 by Felicia West
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weka.BayesianLogisticRegression(2)Alexander Genkin, David D. Lewis, David Madigan (2004). Large-scale bayesian logistic regression for text categorization. URL http://www.stat.rutgers.edu/~madigan/PAPERS/shortFat-v3a.pdf.
weka.BayesianLogisticRegression(2)_Dtrue
weka.BayesianLogisticRegression(2)_F2
weka.BayesianLogisticRegression(2)_H1
weka.BayesianLogisticRegression(2)_I100
weka.BayesianLogisticRegression(2)_Ntrue
weka.BayesianLogisticRegression(2)_P1
weka.BayesianLogisticRegression(2)_RR:0.01-316,3.16
weka.BayesianLogisticRegression(2)_S0.5
weka.BayesianLogisticRegression(2)_Tl5.0E-4
weka.BayesianLogisticRegression(2)_V0.27
weka.BayesianLogisticRegression(2)_seed1

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.

21 Evaluation measures

Area under ROC curve
0.8076
Per class
Build CPU time
0.0151
Build memory
848095384
F measure
0.7986
Per class
Kappa
0.5964
KB relative information score
42.818
Mean absolute error
0.2027
Mean prior absolute error
0.4872
Number of instances
74
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8142
Per class
Predictive accuracy
0.7973
Prior entropy
0.9819
Recall
0.7973
Per class
Relative absolute error
0.4161
Root mean prior squared error
0.4934
Root mean squared error
0.4502
Root relative squared error
0.9125
SciMark benchmark
943.6737

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