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java.lang.Objectweka.classifiers.Classifier
weka.classifiers.rules.DecisionTable
weka.classifiers.rules.DTNB
public class DTNB
Class for building and using a decision table/naive bayes hybrid classifier. At each point in the search, the algorithm evaluates the merit of dividing the attributes into two disjoint subsets: one for the decision table, the other for naive Bayes. A forward selection search is used, where at each step, selected attributes are modeled by naive Bayes and the remainder by the decision table, and all attributes are modelled by the decision table initially. At each step, the algorithm also considers dropping an attribute entirely from the model.
For more information, see:
Mark Hall, Eibe Frank: Combining Naive Bayes and Decision Tables. In: Proceedings of the 21st Florida Artificial Intelligence Society Conference (FLAIRS), ???-???, 2008.
@inproceedings{Hall2008,
author = {Mark Hall and Eibe Frank},
booktitle = {Proceedings of the 21st Florida Artificial Intelligence Society Conference (FLAIRS)},
pages = {318-319},
publisher = {AAAI press},
title = {Combining Naive Bayes and Decision Tables},
year = {2008}
}
Valid options are:
-X <number of folds> Use cross validation to evaluate features. Use number of folds = 1 for leave one out CV. (Default = leave one out CV)
-E <acc | rmse | mae | auc> Performance evaluation measure to use for selecting attributes. (Default = accuracy for discrete class and rmse for numeric class)
-I Use nearest neighbour instead of global table majority.
-R Display decision table rules.
| Field Summary |
|---|
| Fields inherited from class weka.classifiers.rules.DecisionTable |
|---|
EVAL_ACCURACY, EVAL_AUC, EVAL_DEFAULT, EVAL_MAE, EVAL_RMSE, TAGS_EVALUATION |
| Constructor Summary | |
|---|---|
DTNB()
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| Method Summary | |
|---|---|
void |
buildClassifier(Instances data)
Generates the classifier. |
double[] |
distributionForInstance(Instance instance)
Calculates the class membership probabilities for the given test instance. |
java.util.Enumeration |
enumerateMeasures()
Returns an enumeration of the additional measure names |
Capabilities |
getCapabilities()
Returns default capabilities of the classifier. |
double |
getMeasure(java.lang.String additionalMeasureName)
Returns the value of the named measure |
java.lang.String[] |
getOptions()
Gets the current settings of the classifier. |
java.lang.String |
getRevision()
Returns the revision string. |
ASSearch |
getSearch()
Gets the current search method |
TechnicalInformation |
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. |
java.lang.String |
globalInfo()
Returns a string describing classifier |
java.util.Enumeration |
listOptions()
Returns an enumeration describing the available options. |
static void |
main(java.lang.String[] argv)
Main method for testing this class. |
double |
measurePercentAttsUsedByDT()
Returns the number of rules |
void |
setOptions(java.lang.String[] options)
Parses the options for this object. |
void |
setSearch(ASSearch search)
Sets the search method to use |
java.lang.String |
toString()
Returns a description of the classifier. |
| Methods inherited from class weka.classifiers.rules.DecisionTable |
|---|
crossValTipText, displayRulesTipText, evaluationMeasureTipText, getCrossVal, getDisplayRules, getEvaluationMeasure, getUseIBk, measureNumRules, printFeatures, searchTipText, setCrossVal, setDisplayRules, setEvaluationMeasure, setUseIBk, useIBkTipText |
| Methods inherited from class weka.classifiers.Classifier |
|---|
classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug |
| Methods inherited from class java.lang.Object |
|---|
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
| Constructor Detail |
|---|
public DTNB()
| Method Detail |
|---|
public java.lang.String globalInfo()
globalInfo in class DecisionTablepublic TechnicalInformation getTechnicalInformation()
getTechnicalInformation in interface TechnicalInformationHandlergetTechnicalInformation in class DecisionTable
public void buildClassifier(Instances data)
throws java.lang.Exception
buildClassifier in class DecisionTabledata - set of instances serving as training data
java.lang.Exception - if the classifier has not been generated successfully
public double[] distributionForInstance(Instance instance)
throws java.lang.Exception
distributionForInstance in class DecisionTableinstance - the instance to be classified
java.lang.Exception - if distribution can't be computedpublic java.lang.String toString()
DecisionTable
toString in class DecisionTablepublic double measurePercentAttsUsedByDT()
public java.util.Enumeration enumerateMeasures()
enumerateMeasures in interface AdditionalMeasureProducerenumerateMeasures in class DecisionTablepublic double getMeasure(java.lang.String additionalMeasureName)
getMeasure in interface AdditionalMeasureProducergetMeasure in class DecisionTableadditionalMeasureName - the name of the measure to query for its value
java.lang.IllegalArgumentException - if the named measure is not supportedpublic Capabilities getCapabilities()
getCapabilities in interface CapabilitiesHandlergetCapabilities in class DecisionTableCapabilitiespublic void setSearch(ASSearch search)
setSearch in class DecisionTablesearch - public ASSearch getSearch()
getSearch in class DecisionTablepublic java.util.Enumeration listOptions()
listOptions in interface OptionHandlerlistOptions in class DecisionTable
public void setOptions(java.lang.String[] options)
throws java.lang.Exception
-X <number of folds> Use cross validation to evaluate features. Use number of folds = 1 for leave one out CV. (Default = leave one out CV)
-E <acc | rmse | mae | auc> Performance evaluation measure to use for selecting attributes. (Default = accuracy for discrete class and rmse for numeric class)
-I Use nearest neighbour instead of global table majority.
-R Display decision table rules.
setOptions in interface OptionHandlersetOptions in class DecisionTableoptions - the list of options as an array of strings
java.lang.Exception - if an option is not supportedpublic java.lang.String[] getOptions()
getOptions in interface OptionHandlergetOptions in class DecisionTablepublic java.lang.String getRevision()
getRevision in interface RevisionHandlergetRevision in class DecisionTablepublic static void main(java.lang.String[] argv)
argv - the command-line options
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