DEVELOPMENT... OpenML
Run
145180

Run 145180

Task 3909 (Supervised Classification) ar1 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
0.381
Per class
F measure
0.5412
Per class
Kappa
-0.0601
KB relative information score
-530.3496
Mean absolute error
0.5785
Mean prior absolute error
0.1436
Number of instances
121
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8261
Per class
Predictive accuracy
0.4215
Prior entropy
0.4067
Recall
0.4215
Per class
Relative absolute error
4.029
Root mean prior squared error
0.2625
Root mean squared error
0.7606
Root relative squared error
2.8977
SciMark benchmark
902.4773