meta
This category contains 34 nodes.
AdaBoostM1 (3.7)
Class for boosting a nominal class classifier using the Adaboost M1 method
AdditiveRegression (3.7)
Meta classifier that enhances the performance of a regression base classifier
AttributeSelectedClassifier (3.7)
Dimensionality of training and test data is reduced by attribute selection before being passed on to a classifier
Bagging (3.7)
Class for bagging a classifier to reduce variance
ClassificationViaClustering (3.7)
A simple meta-classifier that uses a clusterer for classification
ClassificationViaRegression (3.7)
Class for doing classification using regression methods
CostSensitiveClassifier (3.7)
A metaclassifier that makes its base classifier cost-sensitive
CVParameterSelection (3.7)
Class for performing parameter selection by cross-validation for any classifier. For more information, see: R
Dagging (3.7)
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