DEVELOPMENT... OpenML
Run
86891

Run 86891

Task 241 (Supervised Classification) balance-scale Uploaded 03-12-2014 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)_I10
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
0.8876
Per class
Build CPU time
0.144
Build memory
744591408
F measure
0.791
Per class
Kappa
0.7014
KB relative information score
64.2512
Mean absolute error
0.2824
Mean prior absolute error
0.3857
Number of instances
206
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7572
Per class
Predictive accuracy
0.835
Prior entropy
1.3212
Recall
0.835
Per class
Relative absolute error
0.7321
Root mean prior squared error
0.4424
Root mean squared error
0.3542
Root relative squared error
0.8007
SciMark benchmark
926.0021