Uses of Class
weka.classifiers.meta.multisearch.AbstractSearch

Packages that use AbstractSearch

Package	Description
weka.classifiers.meta
weka.classifiers.meta.multisearch

Uses of AbstractSearch in weka.classifiers.meta

Methods in weka.classifiers.meta that return AbstractSearch

Modifier and Type	Method and Description
AbstractSearch	MultiSearch.defaultAlgorithm() Creates the default search algorithm.
AbstractSearch	MultiSearch.getAlgorithm() Returns the search algorithm.

Methods in weka.classifiers.meta with parameters of type AbstractSearch

Modifier and Type	Method and Description
void	MultiSearch.setAlgorithm(AbstractSearch value) Sets the search algorithm.

Uses of AbstractSearch in weka.classifiers.meta.multisearch

Subclasses of AbstractSearch in weka.classifiers.meta.multisearch

Modifier and Type	Class and Description
class	AbstractMultiThreadedSearch Ancestor for multi-threaded searches.
class	DefaultSearch Performs a search of an arbitrary number of parameters of a classifier and chooses the best setup found for the actual training. The properties being explored are totally up to the user. E.g., if you have a FilteredClassifier selected as base classifier, sporting a PLSFilter and you want to explore the number of PLS components, then your property will be made up of the following components: - filter: referring to the FilteredClassifier's property (= PLSFilter) - numComponents: the actual property of the PLSFilter that we want to modify And assembled, the property looks like this: filter.numComponents The initial space is worked on with 2-fold CV to determine the values of the parameters for the selected type of evaluation (e.g., accuracy).
class	RandomSearch Performs a search of an arbitrary number of parameters of a classifier and chooses the best pair found for the actual filtering and training. Valid options are:

Methods in weka.classifiers.meta.multisearch that return AbstractSearch

Modifier and Type	Method and Description
AbstractSearch	MultiSearchCapable.getAlgorithm() Returns the search algorithm.