cc.mallet.classify
Class DecisionTree.Node

java.lang.Object
  extended by cc.mallet.classify.DecisionTree.Node
All Implemented Interfaces:
java.io.Serializable
Enclosing class:
DecisionTree

public static class DecisionTree.Node
extends java.lang.Object
implements java.io.Serializable

See Also:
Serialized Form

Constructor Summary
DecisionTree.Node(InstanceList ilist, DecisionTree.Node parent, FeatureSelection fs)
           
 
Method Summary
 int depth()
          The root has depth zero.
 DecisionTree.Node getFeatureAbsentChild()
           
 DecisionTree.Node getFeaturePresentChild()
           
 java.lang.String getName()
           
 java.lang.Object getSplitFeature()
           
 double getSplitInfoGain()
           
 void induceFeatures(AugmentableFeatureVector afv, FeatureSelection featuresAlreadyThere, FeatureSelection[] perClassFeaturesAlreadyThere, FeatureSelection newFeatureSelection, FeatureSelection[] perClassNewFeatureSelection, boolean withInteriorNodes, boolean addPerClassFeatures, double classEntropyThreshold)
           
 boolean isLeaf()
           
 boolean isRoot()
           
 void print()
           
 void split(FeatureSelection fs)
           
 void stopGrowth()
           
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

DecisionTree.Node

public DecisionTree.Node(InstanceList ilist,
                         DecisionTree.Node parent,
                         FeatureSelection fs)
Method Detail

depth

public int depth()
The root has depth zero.


isLeaf

public boolean isLeaf()

isRoot

public boolean isRoot()

getFeatureAbsentChild

public DecisionTree.Node getFeatureAbsentChild()

getFeaturePresentChild

public DecisionTree.Node getFeaturePresentChild()

getSplitInfoGain

public double getSplitInfoGain()

getSplitFeature

public java.lang.Object getSplitFeature()

split

public void split(FeatureSelection fs)

stopGrowth

public void stopGrowth()

induceFeatures

public void induceFeatures(AugmentableFeatureVector afv,
                           FeatureSelection featuresAlreadyThere,
                           FeatureSelection[] perClassFeaturesAlreadyThere,
                           FeatureSelection newFeatureSelection,
                           FeatureSelection[] perClassNewFeatureSelection,
                           boolean withInteriorNodes,
                           boolean addPerClassFeatures,
                           double classEntropyThreshold)

getName

public java.lang.String getName()

print

public void print()