Uses of Class
weka.classifiers.SingleClassifierEnhancer
Package
Description
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Uses of SingleClassifierEnhancer in weka.classifiers
Modifier and TypeClassDescriptionclass
Abstract utility class for handling settings common to meta classifiers that build an ensemble from a single base learner.class
Abstract utility class for handling settings common to meta classifiers that build an ensemble in parallel from a single base learner.class
Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from a single base learner.class
Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble in parallel from a single base learner.class
Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from a single base learner. -
Uses of SingleClassifierEnhancer in weka.classifiers.lazy
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Uses of SingleClassifierEnhancer in weka.classifiers.meta
Modifier and TypeClassDescriptionclass
Class for boosting a nominal class classifier using the Adaboost M1 method.class
Meta classifier that enhances the performance of a regression base classifier.class
Dimensionality of training and test data is reduced by attribute selection before being passed on to a classifier.class
Class for bagging a classifier to reduce variance.class
Class for doing classification using regression methods.class
A metaclassifier that makes its base classifier cost sensitive.class
Class for performing parameter selection by cross-validation for any classifier.
For more information, see:
R.class
Class for running an arbitrary classifier on data that has been passed through an arbitrary filter.class
Class for performing additive logistic regression.class
A metaclassifier for handling multi-class datasets with 2-class classifiers.class
A metaclassifier for handling multi-class datasets with 2-class classifiers.class
Class for building an ensemble of randomizable base classifiers.class
Class for running an arbitrary classifier on data that has been passed through an arbitrary filter.class
This method constructs a decision tree based classifier that maintains highest accuracy on training data and improves on generalization accuracy as it grows in complexity.class
A regression scheme that employs any classifier on a copy of the data that has the class attribute (equal-width) discretized.class
Generic wrapper around any classifier to enable weighted instances support.
Uses resampling with weights if the base classifier is not implementing the weka.core.WeightedInstancesHandler interface and there are instance weights other 1.0 present. -
Uses of SingleClassifierEnhancer in weka.classifiers.misc
Modifier and TypeClassDescriptionclass
Wrapper classifier that addresses incompatible training and test data by building a mapping between the training data that a classifier has been built with and the incoming test instances' structure. -
Uses of SingleClassifierEnhancer in weka.classifiers.trees
Modifier and TypeClassDescriptionclass
Class for constructing a forest of random trees.
For more information see:
Leo Breiman (2001).