weka.classifiers.trees.j48
Class C45PruneableClassifierTree

java.lang.Object
  extended by weka.classifiers.trees.j48.ClassifierTree
      extended by 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.

Version:
$Revision: 5535 $
Author:
Eibe Frank (eibe@cs.waikato.ac.nz)
See Also:
Serialized Form

Field Summary
 
Fields inherited from interface weka.core.Drawable
BayesNet, NOT_DRAWABLE, TREE
 
Constructor Summary
C45PruneableClassifierTree(ModelSelection toSelectLocModel, boolean pruneTree, float cf, boolean raiseTree, boolean cleanup)
          Constructor for pruneable tree structure.
 
Method Summary
 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.
 Capabilities getCapabilities()
          Returns default capabilities of the classifier tree.
 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, graph, graphType, 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)
                           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

getCapabilities

public Capabilities getCapabilities()
Returns default capabilities of the classifier tree.

Specified by:
getCapabilities in interface CapabilitiesHandler
Overrides:
getCapabilities in class ClassifierTree
Returns:
the capabilities of this classifier tree
See Also:
Capabilities

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