Package weka.classifiers.trees
Class NBTree
java.lang.Object
weka.classifiers.Classifier
weka.classifiers.trees.NBTree
- All Implemented Interfaces:
Serializable
,Cloneable
,AdditionalMeasureProducer
,CapabilitiesHandler
,Drawable
,OptionHandler
,RevisionHandler
,Summarizable
,TechnicalInformationHandler
,WeightedInstancesHandler
public class NBTree
extends Classifier
implements WeightedInstancesHandler, Drawable, Summarizable, AdditionalMeasureProducer, TechnicalInformationHandler
Class for generating a decision tree with naive Bayes classifiers at the leaves.
For more information, see
Ron Kohavi: Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid. In: Second International Conference on Knoledge Discovery and Data Mining, 202-207, 1996. BibTeX:
For more information, see
Ron Kohavi: Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid. In: Second International Conference on Knoledge Discovery and Data Mining, 202-207, 1996. BibTeX:
@inproceedings{Kohavi1996, author = {Ron Kohavi}, booktitle = {Second International Conference on Knoledge Discovery and Data Mining}, pages = {202-207}, title = {Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid}, year = {1996} }Valid options are:
-D If set, classifier is run in debug mode and may output additional info to the console
- Version:
- $Revision: 1.10 $
- Author:
- Mark Hall
- See Also:
-
Field Summary
Fields inherited from interface weka.core.Drawable
BayesNet, Newick, NOT_DRAWABLE, TREE
-
Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionvoid
buildClassifier
(Instances instances) Generates the classifier.double
classifyInstance
(Instance instance) Classifies an instance.final double[]
distributionForInstance
(Instance instance) Returns class probabilities for an instance.Returns an enumeration of the additional measure namesReturns default capabilities of the classifier.double
getMeasure
(String additionalMeasureName) Returns the value of the named measureReturns the revision string.Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.Returns a string describing classifiergraph()
Returns graph describing the tree.int
Returns the type of graph this classifier represents.static void
Main method for testing this classdouble
Returns the number of leavesdouble
Returns the number of rules (same as number of leaves)double
Returns the size of the treetoString()
Returns a description of the classifier.Returns a superconcise version of the modelMethods inherited from class weka.classifiers.Classifier
debugTipText, forName, getDebug, getOptions, listOptions, makeCopies, makeCopy, setDebug, setOptions
-
Constructor Details
-
NBTree
public NBTree()
-
-
Method Details
-
globalInfo
Returns a string describing classifier- Returns:
- a description suitable for displaying in the explorer/experimenter gui
-
getTechnicalInformation
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.- Specified by:
getTechnicalInformation
in interfaceTechnicalInformationHandler
- Returns:
- the technical information about this class
-
getCapabilities
Returns default capabilities of the classifier.- Specified by:
getCapabilities
in interfaceCapabilitiesHandler
- Overrides:
getCapabilities
in classClassifier
- Returns:
- the capabilities of this classifier
- See Also:
-
buildClassifier
Generates the classifier.- Specified by:
buildClassifier
in classClassifier
- Parameters:
instances
- the data to train with- Throws:
Exception
- if classifier can't be built successfully
-
classifyInstance
Classifies an instance.- Overrides:
classifyInstance
in classClassifier
- Parameters:
instance
- the instance to classify- Returns:
- the classification
- Throws:
Exception
- if instance can't be classified successfully
-
distributionForInstance
Returns class probabilities for an instance.- Overrides:
distributionForInstance
in classClassifier
- Parameters:
instance
- the instance to get the distribution for- Returns:
- the class probabilities
- Throws:
Exception
- if distribution can't be computed successfully
-
toString
Returns a description of the classifier. -
graphType
public int graphType()Returns the type of graph this classifier represents. -
graph
Returns graph describing the tree. -
toSummaryString
Returns a superconcise version of the model- Specified by:
toSummaryString
in interfaceSummarizable
- Returns:
- a description of the model
-
measureTreeSize
public double measureTreeSize()Returns the size of the tree- Returns:
- the size of the tree
-
measureNumLeaves
public double measureNumLeaves()Returns the number of leaves- Returns:
- the number of leaves
-
measureNumRules
public double measureNumRules()Returns the number of rules (same as number of leaves)- Returns:
- the number of rules
-
getMeasure
Returns the value of the named measure- Specified by:
getMeasure
in interfaceAdditionalMeasureProducer
- Parameters:
additionalMeasureName
- the name of the measure to query for its value- Returns:
- the value of the named measure
- Throws:
IllegalArgumentException
- if the named measure is not supported
-
enumerateMeasures
Returns an enumeration of the additional measure names- Specified by:
enumerateMeasures
in interfaceAdditionalMeasureProducer
- Returns:
- an enumeration of the measure names
-
getRevision
Returns the revision string.- Specified by:
getRevision
in interfaceRevisionHandler
- Overrides:
getRevision
in classClassifier
- Returns:
- the revision
-
main
Main method for testing this class- Parameters:
argv
- the commandline options
-