Uses of Class
weka.classifiers.RandomizableSingleClassifierEnhancer

Packages that use RandomizableSingleClassifierEnhancer

weka.classifiers.meta
weka.classifiers.meta.nestedDichotomies

Uses of RandomizableSingleClassifierEnhancer in weka.classifiers.meta

Subclasses of RandomizableSingleClassifierEnhancer in weka.classifiers.meta

class	CostSensitiveClassifier A metaclassifier that makes its base classifier cost-sensitive.
class	CVParameterSelection Class for performing parameter selection by cross-validation for any classifier. For more information, see: R.
class	Dagging This meta classifier creates a number of disjoint, stratified folds out of the data and feeds each chunk of data to a copy of the supplied base classifier.
class	GridSearch Performs a grid search of parameter pairs for the a classifier (Y-axis, default is LinearRegression with the "Ridge" parameter) and the PLSFilter (X-axis, "# of Components") and chooses the best pair found for the actual predicting. The initial grid is worked on with 2-fold CV to determine the values of the parameter pairs for the selected type of evaluation (e.g., accuracy).
class	MetaCost This metaclassifier makes its base classifier cost-sensitive using the method specified in Pedro Domingos: MetaCost: A general method for making classifiers cost-sensitive.
class	MultiClassClassifier A metaclassifier for handling multi-class datasets with 2-class classifiers.
class	RacedIncrementalLogitBoost Classifier for incremental learning of large datasets by way of racing logit-boosted committees. For more information see: Eibe Frank, Geoffrey Holmes, Richard Kirkby, Mark Hall: Racing committees for large datasets.
class	ThresholdSelector A metaclassifier that selecting a mid-point threshold on the probability output by a Classifier.

Uses of RandomizableSingleClassifierEnhancer in weka.classifiers.meta.nestedDichotomies

Subclasses of RandomizableSingleClassifierEnhancer in weka.classifiers.meta.nestedDichotomies

class	ClassBalancedND A meta classifier for handling multi-class datasets with 2-class classifiers by building a random class-balanced tree structure. For more info, check Lin Dong, Eibe Frank, Stefan Kramer: Ensembles of Balanced Nested Dichotomies for Multi-class Problems.
class	DataNearBalancedND A meta classifier for handling multi-class datasets with 2-class classifiers by building a random data-balanced tree structure. For more info, check Lin Dong, Eibe Frank, Stefan Kramer: Ensembles of Balanced Nested Dichotomies for Multi-class Problems.
class	ND A meta classifier for handling multi-class datasets with 2-class classifiers by building a random tree structure. For more info, check Lin Dong, Eibe Frank, Stefan Kramer: Ensembles of Balanced Nested Dichotomies for Multi-class Problems.