WrapperSubsetEval
Package
weka.attributeSelection
Synopsis
WrapperSubsetEval:
Evaluates attribute sets by using a learning scheme. Cross validation is used to estimate the accuracy of the learning scheme for a set of attributes.
For more information see:
Ron Kohavi, George H. John (1997). Wrappers for feature subset selection. Artificial Intelligence. 97(1-2):273-324.
Options
The table below describes the options available for WrapperSubsetEval.
Option |
Description |
|---|---|
classifier |
Classifier to use for estimating the accuracy of subsets |
evaluationMeasure |
The measure used to evaluate the performance of attribute combinations. |
folds |
Number of xval folds to use when estimating subset accuracy. |
seed |
Seed to use for randomly generating xval splits. |
threshold |
Repeat xval if stdev of mean exceeds this value. |
Capabilities
The table below describes the capabilites of WrapperSubsetEval.
Capability |
Supported |
|---|---|
Class |
Date class, Numeric class, Missing class values, Nominal class, Binary class |
Attributes |
Unary attributes, String attributes, Empty nominal attributes, Relational attributes, Missing values, Numeric attributes, Date attributes, Binary attributes, Nominal attributes |
Min # of instances |
5 |