public class CHAIDStarSplit extends CHAIDSplit
Modifier and Type | Field and Description |
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protected static ChiSquareSplitCrit |
chiSquareCrit
Static reference to splitting criterion.
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(package private) int |
m_missingCurrentIndex
Current position for missing values on the attribute to split on.
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protected double |
m_splitPoint
Value of split point.
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private static long |
serialVersionUID
for serialization
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m_attIndex, m_chiSquaredProb, m_complexityIndex, m_index, m_minNoObj, m_missingIdx, m_ordered, m_searchBestSplit, m_sigLevelAtt, m_sigLevelMergeSplit
Constructor and Description |
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CHAIDStarSplit(int attIndex,
int minNoObj,
double sumOfWeights,
boolean useMDLcorrection,
double sigLevelAtt,
double sigLevelMergeSplit,
boolean searchBestSplit,
int minNumObjSplit,
boolean ordered)
Initializes the split model.
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Modifier and Type | Method and Description |
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void |
buildClassifier(weka.core.Instances trainInstances)
Creates a CHAID*-type split on the given data.
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java.lang.String |
getRevision()
Returns the revision string.
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void |
handleNumericAttribute(weka.core.Instances trainInstances)
Creates split on numeric attribute.
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java.lang.String |
rightSide(int index,
weka.core.Instances data)
Prints the condition satisfied by instances in a subset.
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void |
setSplitPoint(weka.core.Instances allInstances)
Sets split point to greatest value in given data smaller or equal to old
split point.
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java.lang.String |
sourceExpression(int index,
weka.core.Instances data)
Returns a string containing java source code equivalent to the test made at
this node.
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int |
whichSubset(weka.core.Instance instance)
Returns index of subset instance is assigned to.
|
chiSquaredProb, getCHAIDDistribution, getMissingCurrentIndex, handleEnumeratedAttribute, hasMissingValues, leftSide, resetDistribution, split, weights
private static final long serialVersionUID
protected double m_splitPoint
protected static ChiSquareSplitCrit chiSquareCrit
int m_missingCurrentIndex
public CHAIDStarSplit(int attIndex, int minNoObj, double sumOfWeights, boolean useMDLcorrection, double sigLevelAtt, double sigLevelMergeSplit, boolean searchBestSplit, int minNumObjSplit, boolean ordered)
attIndex
- Attribute to split onminNoObj
- minimum number of instances that have to occur in at least
two subsets induced by splitsumOfWeights
- sum of the weightsuseMDLcorrection
- whether to use MDL adjustement when finding splits
on numeric attributessigLevel
- Significance level for the selection of attributesordered
- true if the nature of the categories is orderedpublic void buildClassifier(weka.core.Instances trainInstances) throws java.lang.Exception
buildClassifier
in class CHAIDSplit
java.lang.Exception
- if something goes wrongpublic void handleNumericAttribute(weka.core.Instances trainInstances) throws java.lang.Exception
java.lang.Exception
- if something goes wrongpublic final int whichSubset(weka.core.Instance instance) throws java.lang.Exception
whichSubset
in class CHAIDSplit
java.lang.Exception
- if something goes wrongpublic final java.lang.String rightSide(int index, weka.core.Instances data)
rightSide
in class CHAIDSplit
index
- of subsetdata
- training set.public final java.lang.String sourceExpression(int index, weka.core.Instances data)
sourceExpression
in class CHAIDSplit
index
- index of the nominal value testeddata
- the data containing instance structure infopublic final void setSplitPoint(weka.core.Instances allInstances)
public java.lang.String getRevision()
getRevision
in interface weka.core.RevisionHandler
getRevision
in class CHAIDSplit