CVParameterSelection

Package

weka.classifiers.meta

Class for performing parameter selection by cross-validation for any classifier.

For more information, see:

R. Kohavi (1995). Wrappers for Performance Enhancement and Oblivious Decision Graphs. Department of Computer Science, Stanford University.

The table below describes the options available for CVParameterSelection.

Option	Description
CVParameters	Sets the scheme parameters which are to be set by cross-validation. The format for each string should be: param_char lower_bound upper_bound number_of_steps eg to search a parameter -P from 1 to 10 by increments of 1: "P 1 10 11"
classifier	The base classifier to be used.
debug	If set to true, classifier may output additional info to the console.
numFolds	Get the number of folds used for cross-validation.
seed	The random number seed to be used.

The table below describes the capabilites of CVParameterSelection.

Capability	Supported
Class	Date class, Numeric class, Nominal class, Binary class, Missing class values
Attributes	Unary attributes, Date attributes, Missing values, Binary attributes, Relational attributes, Empty nominal attributes, String attributes, Nominal attributes, Numeric attributes
Min # of instances	10