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