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## 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.

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, Newick, 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

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