DEVELOPMENT... OpenML
Run
145005

Run 145005

Task 3721 (Supervised Classification) bolts Uploaded 31-01-2015 by Felicia West
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Flow

weka.AdaBoostM1_BayesianLogisticRegression(2)Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
weka.AdaBoostM1_BayesianLogisticRegression(2)_I10
weka.AdaBoostM1_BayesianLogisticRegression(2)_P100
weka.AdaBoostM1_BayesianLogisticRegression(2)_S1
weka.AdaBoostM1_BayesianLogisticRegression(2)_Wweka.classifiers.bayes.BayesianLogisticRegression
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.

22 Evaluation measures

Area under ROC curve
0.5385
Per class
F measure
0.2813
Per class
Kappa
0.0551
KB relative information score
-14.4418
Mean absolute error
0.6
Mean prior absolute error
0.4571
Number of instances
40
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7789
Per class
Predictive accuracy
0.4
Prior entropy
0.9403
Recall
0.4
Per class
Relative absolute error
1.3125
Root mean prior squared error
0.477
Root mean squared error
0.7746
Root relative squared error
1.6238
SciMark benchmark
917.1386