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## weka.classifiers.trees
Class RandomTree

    java.lang.Object
      weka.classifiers.Classifier
          weka.classifiers.trees.RandomTree

All Implemented Interfaces:
  java.io.Serializable, java.lang.Cloneable, OptionHandler, Randomizable, WeightedInstancesHandler

    public class RandomTree

extends Classifier
implements OptionHandler, WeightedInstancesHandler, Randomizable

Class for constructing a tree that considers K random features at each node. Performs no pruning.

Version:
  $Revision: 5291 $
Author:
  Eibe Frank (eibe@cs.waikato.ac.nz), Richard Kirkby (rkirkby@cs.waikato.ac.nz)
See Also:
  Serialized Form

Constructor Summary
`RandomTree()`

Method Summary
`void` | `buildClassifier(Instances data)` Builds classifier.
`java.lang.String` | `debugTipText()` Returns the tip text for this property
`double[]` | `distributionForInstance(Instance instance)` Computes class distribution of an instance using the decision tree.
`boolean` | `getDebug()` Get the value of Debug.
`int` | `getKValue()` Get the value of K.
`double` | `getMinNum()` Get the value of MinNum.
`java.lang.String[]` | `getOptions()` Gets options from this classifier.
`int` | `getSeed()` Gets the seed for the random number generations
`java.lang.String` | `globalInfo()` Returns a string describing classifier
`java.lang.String` | `KValueTipText()` Returns the tip text for this property
`java.util.Enumeration` | `listOptions()` Lists the command-line options for this classifier.
`static void` | `main(java.lang.String[] argv)` Main method for this class.
`java.lang.String` | `minNumTipText()` Returns the tip text for this property
`int` | `numNodes()` Computes size of the tree.
`java.lang.String` | `seedTipText()` Returns the tip text for this property
`void` | `setDebug(boolean newDebug)` Set the value of Debug.
`void` | `setKValue(int k)` Set the value of K.
`void` | `setMinNum(double newMinNum)` Set the value of MinNum.
`void` | `setOptions(java.lang.String[] options)` Parses a given list of options.
`void` | `setSeed(int seed)` Set the seed for random number generation.
`java.lang.String` | `toGraph()` Outputs the decision tree as a graph
`int` | `toGraph(java.lang.StringBuffer text, int num)` Outputs one node for graph.
`java.lang.String` | `toString()` Outputs the decision tree.

Methods inherited from class weka.classifiers.Classifier
`classifyInstance, forName, makeCopies, makeCopy`

Methods inherited from class java.lang.Object
`equals, getClass, hashCode, notify, notifyAll, wait, wait, wait`

Constructor Detail

### RandomTree

    public RandomTree()

Method Detail

### globalInfo

    public java.lang.String globalInfo()

  Returns a string describing classifier

  Returns:
    a description suitable for displaying in the explorer/experimenter gui

### minNumTipText

    public java.lang.String minNumTipText()

  Returns the tip text for this property

  Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui

### getMinNum

    public double getMinNum()

  Get the value of MinNum.

  Returns:
    Value of MinNum.

### setMinNum

    public void setMinNum(double newMinNum)

  Set the value of MinNum.

  Parameters:
    `newMinNum` - Value to assign to MinNum.

### KValueTipText

    public java.lang.String KValueTipText()

  Returns the tip text for this property

  Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui

### getKValue

    public int getKValue()

  Get the value of K.

  Returns:
    Value of K.

### setKValue

    public void setKValue(int k)

  Set the value of K.

  Parameters:
    `k` - Value to assign to K.

### debugTipText

    public java.lang.String debugTipText()

  Returns the tip text for this property

  Overrides:
    `debugTipText` in class `Classifier`
  Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui

### getDebug

    public boolean getDebug()

  Get the value of Debug.

  Overrides:
    `getDebug` in class `Classifier`
  Returns:
    Value of Debug.

### setDebug

    public void setDebug(boolean newDebug)

  Set the value of Debug.

  Overrides:
    `setDebug` in class `Classifier`
  Parameters:
    `newDebug` - Value to assign to Debug.

### seedTipText

    public java.lang.String seedTipText()

  Returns the tip text for this property

  Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui

### setSeed

    public void setSeed(int seed)

  Set the seed for random number generation.

  Specified by:
    `setSeed` in interface `Randomizable`
  Parameters:
    `seed` - the seed

### getSeed

    public int getSeed()

  Gets the seed for the random number generations

  Specified by:
    `getSeed` in interface `Randomizable`
  Returns:
    the seed for the random number generation

### listOptions

    public java.util.Enumeration listOptions()

  Lists the command-line options for this classifier.

  Specified by:
    `listOptions` in interface `OptionHandler`
  Overrides:
    `listOptions` in class `Classifier`
  Returns:
    an enumeration of all the available options.

### getOptions

    public java.lang.String[] getOptions()

  Gets options from this classifier.

  Specified by:
    `getOptions` in interface `OptionHandler`
  Overrides:
    `getOptions` in class `Classifier`
  Returns:
    an array of strings suitable for passing to setOptions

### setOptions

    public void setOptions(java.lang.String[] options)
                    throws java.lang.Exception

  Parses a given list of options.

  Specified by:
    `setOptions` in interface `OptionHandler`
  Overrides:
    `setOptions` in class `Classifier`
  Parameters:
    `options` - the list of options as an array of strings
  Throws:
    `java.lang.Exception` - if an option is not supported

### buildClassifier

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

  Builds classifier.

  Specified by:
    `buildClassifier` in class `Classifier`
  Parameters:
    `data` - set of instances serving as training data
  Throws:
    `java.lang.Exception` - if the classifier has not been generated successfully

### distributionForInstance

    public double[] distributionForInstance(Instance instance)
                                     throws java.lang.Exception

  Computes class distribution of an instance using the decision tree.

  Overrides:
    `distributionForInstance` in class `Classifier`
  Parameters:
    `instance` - the instance to be classified
  Returns:
    an array containing the estimated membership probabilities of the test instance in each class or the numeric prediction
  Throws:
    `java.lang.Exception` - if distribution could not be computed successfully

### toGraph

    public java.lang.String toGraph()

  Outputs the decision tree as a graph

### toGraph

    public int toGraph(java.lang.StringBuffer text,
                       int num)
                throws java.lang.Exception

  Outputs one node for graph.

  Throws:
    `java.lang.Exception`

### toString

    public java.lang.String toString()

  Outputs the decision tree.

  Overrides:
    `toString` in class `java.lang.Object`

### numNodes

    public int numNodes()

  Computes size of the tree.

### main

    public static void main(java.lang.String[] argv)

  Main method for this class.

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