weka.classifiers.trees.j48

Class C45PruneableClassifierTree

java.lang.Object

weka.classifiers.trees.j48.ClassifierTree

weka.classifiers.trees.j48.C45PruneableClassifierTree

All Implemented Interfaces:

java.io.Serializable, CapabilitiesHandler, Drawable, RevisionHandler

public class C45PruneableClassifierTree
extends ClassifierTree

Class for handling a tree structure that can be pruned using C4.5 procedures.

See Also:

Serialized Form

Field Summary

Fields inherited from interface weka.core.Drawable

BayesNet, Newick, NOT_DRAWABLE, TREE

Constructor Summary

Constructors

Constructor and Description
C45PruneableClassifierTree(ModelSelection toSelectLocModel, boolean pruneTree, float cf, boolean raiseTree, boolean cleanup, boolean collapseTree) Constructor for pruneable tree structure.

Method Summary

Modifier and Type	Method and Description
void	buildClassifier(Instances data) Method for building a pruneable classifier tree.
void	collapse() Collapses a tree to a node if training error doesn't increase.
java.lang.String	getRevision() Returns the revision string.
void	prune() Prunes a tree using C4.5's pruning procedure.

Methods inherited from class weka.classifiers.trees.j48.ClassifierTree

assignIDs, buildTree, buildTree, classifyInstance, cleanup, distributionForInstance, getCapabilities, getLocalModel, getMembershipValues, getSons, getTrainingData, graph, graphType, isLeaf, numLeaves, numNodes, prefix, toSource, toString

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

C45PruneableClassifierTree

public C45PruneableClassifierTree(ModelSelection toSelectLocModel,
                                  boolean pruneTree,
                                  float cf,
                                  boolean raiseTree,
                                  boolean cleanup,
                                  boolean collapseTree)
                           throws java.lang.Exception

Constructor for pruneable tree structure. Stores reference to associated training data at each node.

Parameters:

toSelectLocModel - selection method for local splitting model

pruneTree - true if the tree is to be pruned

cf - the confidence factor for pruning

raiseTree -

cleanup -

Throws:

java.lang.Exception - if something goes wrong

Method Detail

buildClassifier

public void buildClassifier(Instances data)
                     throws java.lang.Exception

Method for building a pruneable classifier tree.

Overrides:

buildClassifier in class ClassifierTree

Parameters:

data - the data for building the tree

Throws:

java.lang.Exception - if something goes wrong

collapse

public final void collapse()

Collapses a tree to a node if training error doesn't increase.

prune

public void prune()
           throws java.lang.Exception

Prunes a tree using C4.5's pruning procedure.

Throws:

java.lang.Exception - if something goes wrong

getRevision

public java.lang.String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class ClassifierTree

Returns:

the revision