DEVELOPMENT... OpenML
Run
83958

Run 83958

Task 3849 (Supervised Classification) analcatdata_marketing Uploaded 02-12-2014 by Felicia West
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Flow

weka.Bagging_SMO_PolyKernel(2)Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
weka.Bagging_SMO_PolyKernel(2)_I80
weka.Bagging_SMO_PolyKernel(2)_P100
weka.Bagging_SMO_PolyKernel(2)_S1
weka.Bagging_SMO_PolyKernel(2)_Wweka.classifiers.functions.SMO
weka.Bagging_SMO_PolyKernel(2)_num-slots1
weka.SMO_PolyKernel(7)_C1.0
weka.SMO_PolyKernel(7)_L0.001
weka.SMO_PolyKernel(7)_N0
weka.SMO_PolyKernel(7)_P1.0E-12
weka.SMO_PolyKernel(7)_V-1
weka.SMO_PolyKernel(7)_W1

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
0.5211
Per class
Build CPU time
17.234
Build memory
599559905.956
F measure
0.5932
Per class
Kappa
0.0398
KB relative information score
-18.4723
Mean absolute error
0.4316
Mean prior absolute error
0.4326
Number of instances
364
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.5853
Per class
Predictive accuracy
0.6044
Prior entropy
0.901
Recall
0.6044
Per class
Relative absolute error
0.9977
Root mean prior squared error
0.4649
Root mean squared error
0.5204
Root relative squared error
1.1195
SciMark benchmark
946.5993