Uses of Interface
weka.core.Drawable

Packages that use Drawable

weka.classifiers.bayes
weka.classifiers.bayes.net
weka.classifiers.meta
weka.classifiers.trees
weka.classifiers.trees.j48
weka.clusterers

Uses of Drawable in weka.classifiers.bayes

Classes in weka.classifiers.bayes that implement Drawable

class

BayesNet 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

Classes in weka.classifiers.bayes.net that implement Drawable

class	BayesNetGenerator Bayes Network learning using various search algorithms and quality measures. Base class for a Bayes Network classifier.
class	BIFReader 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	EditableBayesNet Bayes Network learning using various search algorithms and quality measures. Base class for a Bayes Network classifier.

Uses of Drawable in weka.classifiers.meta

Classes in weka.classifiers.meta that implement Drawable

class	AttributeSelectedClassifier Dimensionality of training and test data is reduced by attribute selection before being passed on to a classifier.
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	FilteredClassifier Class for running an arbitrary classifier on data that has been passed through an arbitrary filter.
class	ThresholdSelector A metaclassifier that selecting a mid-point threshold on the probability output by a Classifier.

Uses of Drawable in weka.classifiers.trees

Classes in weka.classifiers.trees that implement Drawable

class	ADTree Class for generating an alternating decision tree.
class	FT Classifier for building 'Functional trees', which are classification trees that could have logistic regression functions at the inner nodes and/or leaves.
class	J48 Class for generating a pruned or unpruned C4.5 decision tree.
class	J48graft Class for generating a grafted (pruned or unpruned) C4.5 decision tree.
class	LADTree Class for generating a multi-class alternating decision tree using the LogitBoost strategy.
class	LMT Classifier for building 'logistic model trees', which are classification trees with logistic regression functions at the leaves.
class	M5P M5Base.
class	NBTree Class for generating a decision tree with naive Bayes classifiers at the leaves. For more information, see Ron Kohavi: Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid.
class	RandomTree Class for constructing a tree that considers K randomly chosen attributes at each node.
class	REPTree Fast decision tree learner.
class	UserClassifier Interactively classify through visual means.

Uses of Drawable in weka.classifiers.trees.j48

Classes in weka.classifiers.trees.j48 that implement Drawable

class	C45PruneableClassifierTree Class for handling a tree structure that can be pruned using C4.5 procedures.
class	C45PruneableClassifierTreeG Class for handling a tree structure that can be pruned using C4.5 procedures and have nodes grafted on.
class	ClassifierTree Class for handling a tree structure used for classification.
class	NBTreeClassifierTree Class for handling a naive bayes tree structure used for classification.
class	PruneableClassifierTree Class for handling a tree structure that can be pruned using a pruning set.

Uses of Drawable in weka.clusterers

Classes in weka.clusterers that implement Drawable

class	Cobweb 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	HierarchicalClusterer Hierarchical clustering class.