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java.lang.Objectweka.classifiers.trees.j48.ClassifierSplitModel
weka.classifiers.trees.j48.NBTreeNoSplit
Class implementing a "no-split"-split (leaf node) for naive bayes trees.
Constructor Summary | |
NBTreeNoSplit()
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Method Summary | |
void |
buildClassifier(Instances instances)
Build the no-split node |
double |
classProb(int classIndex,
Instance instance,
int theSubset)
Return the probability for a class value |
static double |
crossValidate(NaiveBayesUpdateable fullModel,
Instances trainingSet,
java.util.Random r)
Utility method for fast 5-fold cross validation of a naive bayes model |
Discretize |
getDiscretizer()
Return the discretizer used at this node |
double |
getErrors()
Return the errors made by the naive bayes model at this node |
NaiveBayesUpdateable |
getNaiveBayesModel()
Get the naive bayes model at this node |
java.lang.String |
leftSide(Instances instances)
Does nothing because no condition has to be satisfied. |
java.lang.String |
rightSide(int index,
Instances instances)
Does nothing because no condition has to be satisfied. |
java.lang.String |
sourceExpression(int index,
Instances data)
Returns a string containing java source code equivalent to the test made at this node. |
java.lang.String |
toString()
Return a textual description of the node |
double[] |
weights(Instance instance)
Always returns null because there is only one subset. |
int |
whichSubset(Instance instance)
Always returns 0 because only there is only one subset. |
Methods inherited from class weka.classifiers.trees.j48.ClassifierSplitModel |
checkModel, classifyInstance, classProbLaplace, clone, codingCost, distribution, dumpLabel, dumpModel, numSubsets, resetDistribution, sourceClass, split |
Methods inherited from class java.lang.Object |
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Constructor Detail |
public NBTreeNoSplit()
Method Detail |
public final void buildClassifier(Instances instances) throws java.lang.Exception
buildClassifier
in class ClassifierSplitModel
instances
- an Instances
value
java.lang.Exception
- if an error occurspublic double getErrors()
public Discretize getDiscretizer()
Discretize
valuepublic NaiveBayesUpdateable getNaiveBayesModel()
NaiveBayesUpdateable
valuepublic final int whichSubset(Instance instance)
whichSubset
in class ClassifierSplitModel
public final double[] weights(Instance instance)
weights
in class ClassifierSplitModel
public final java.lang.String leftSide(Instances instances)
leftSide
in class ClassifierSplitModel
instances
- the data.public final java.lang.String rightSide(int index, Instances instances)
rightSide
in class ClassifierSplitModel
public final java.lang.String sourceExpression(int index, Instances data)
sourceExpression
in class ClassifierSplitModel
index
- index of the nominal value testeddata
- the data containing instance structure info
public double classProb(int classIndex, Instance instance, int theSubset) throws java.lang.Exception
classProb
in class ClassifierSplitModel
classIndex
- the index of the class valueinstance
- the instance to generate a probability fortheSubset
- the subset to consider
java.lang.Exception
- if an error occurspublic java.lang.String toString()
String
valuepublic static double crossValidate(NaiveBayesUpdateable fullModel, Instances trainingSet, java.util.Random r) throws java.lang.Exception
fullModel
- a NaiveBayesUpdateable
valuetrainingSet
- an Instances
valuer
- a Random
value
double
value
java.lang.Exception
- if an error occurs
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