This category contains 30 nodes.
Class for boosting a nominal class classifier using the Adaboost M1 method.
Meta classifier that enhances the performance of a regression base classifier.
Dimensionality of training and test data is reduced by attribute selection before being passed on to a classifier.
Class for bagging a classifier to reduce variance.
Class for doing classification using regression methods.
A metaclassifier that makes its base classifier cost-sensitive.
Class for performing parameter selection by cross-validation for any classifier.
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 […]
DECORATE is a meta-learner for building diverse ensembles of classifiers by using specially constructed artificial training examples.
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