Uses of Interface
weka.core.Drawable
Package
Description
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Uses of Drawable in weka.classifiers.bayes
Modifier and TypeClassDescriptionclass
Bayes Network learning using various search algorithms and quality measures.
Base class for a Bayes Network classifier. -
Uses of Drawable in weka.classifiers.bayes.net
Modifier and TypeClassDescriptionclass
Bayes Network learning using various search algorithms and quality measures.
Base class for a Bayes Network classifier.class
Builds a description of a Bayes Net classifier stored in XML BIF 0.3 format.
For more details on XML BIF see:
Fabio Cozman, Marek Druzdzel, Daniel Garcia (1998).class
Bayes Network learning using various search algorithms and quality measures.
Base class for a Bayes Network classifier. -
Uses of Drawable in weka.classifiers.meta
Modifier and TypeClassDescriptionclass
Dimensionality of training and test data is reduced by attribute selection before being passed on to a classifier.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 running an arbitrary classifier on data that has been passed through an arbitrary filter. -
Uses of Drawable 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 Drawable in weka.classifiers.pmml.consumer
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Uses of Drawable in weka.classifiers.trees
Modifier and TypeClassDescriptionclass
A Hoeffding tree (VFDT) is an incremental, anytime decision tree induction algorithm that is capable of learning from massive data streams, assuming that the distribution generating examples does not change over time.class
Class for generating a pruned or unpruned C4.5 decision tree.class
Classifier for building 'logistic model trees', which are classification trees with logistic regression functions at the leaves.class
M5Base.class
Class for constructing a tree that considers K randomly chosen attributes at each node.class
Fast decision tree learner. -
Uses of Drawable in weka.classifiers.trees.j48
Modifier and TypeClassDescriptionclass
Class for handling a tree structure that can be pruned using C4.5 procedures.class
Class for handling a tree structure used for classification.class
Class for handling a naive bayes tree structure used for classification.class
Class for handling a tree structure that can be pruned using a pruning set. -
Uses of Drawable in weka.clusterers
Modifier and TypeClassDescriptionclass
Class implementing the Cobweb and Classit clustering algorithms.
Note: the application of node operators (merging, splitting etc.) in terms of ordering and priority differs (and is somewhat ambiguous) between the original Cobweb and Classit papers.class
Class for running an arbitrary clusterer on data that has been passed through an arbitrary filter.class
Hierarchical clustering class.