DEVELOPMENT... OpenML
Run
105936

Run 105936

Task 3539 (Supervised Classification) prnn_crabs Uploaded 09-12-2014 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.

21 Evaluation measures

Area under ROC curve
0.6391
Per class
Build CPU time
0.1588
Build memory
143844814.4
F measure
0.6022
Per class
Kappa
0.22
KB relative information score
20.4724
Mean absolute error
0.456
Mean prior absolute error
0.5
Number of instances
200
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.6194
Per class
Predictive accuracy
0.61
Prior entropy
1
Recall
0.61
Per class
Relative absolute error
0.912
Root mean prior squared error
0.5
Root mean squared error
0.4979
Root relative squared error
0.9958
SciMark benchmark
902.0906