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 |