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## weka.classifiers.bayes
Class DMNBtext

    java.lang.Object
      weka.classifiers.Classifier
          weka.classifiers.bayes.DMNBtext

All Implemented Interfaces:
  java.io.Serializable, java.lang.Cloneable, UpdateableClassifier, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler, WeightedInstancesHandler

    public class DMNBtext

extends Classifier
implements OptionHandler, WeightedInstancesHandler, TechnicalInformationHandler, UpdateableClassifier

Class for building and using a Discriminative Multinomial Naive Bayes classifier. For more information see,
Jiang Su,Harry Zhang,Charles X. Ling,Stan Matwin: Discriminative Parameter Learning for Bayesian Networks. In: ICML 2008', 2008.
The core equation for this classifier:
P[Ci|D] = (P[D|Ci] x P[Ci]) / P[D] (Bayes rule)
where Ci is class i and D is a document.

BibTeX:

     @inproceedings{JiangSu2008,
        author = {Jiang Su,Harry Zhang,Charles X. Ling,Stan Matwin},
        booktitle = {ICML 2008'},
        title = {Discriminative Parameter Learning for Bayesian Networks},
        year = {2008}
     }

Valid options are:

     -I <iterations>
      The number of iterations that the classifier
      will scan the training data (default = 1)

     -M
      Use the frequency information in data

Version:
  $Revision: 6363 $
Author:
  Jiang Su (Jiang.Su@unb.ca) 2008
See Also:
  Serialized Form

Nested Class Summary
`class` | `DMNBtext.DNBBinary`

Constructor Summary
`DMNBtext()`

Method Summary
`void` | `buildClassifier(Instances data)` Generates the classifier.
`double[]` | `distributionForInstance(Instance instance)` Calculates the class membership probabilities for the given test instance.
`Capabilities` | `getCapabilities()` Returns default capabilities of the classifier.
`boolean` | `getMultinomialWord()` Gets whether use binary text representation
`int` | `getNumIterations()` Gets the number of iterations to be performed
`java.lang.String[]` | `getOptions()` Gets the current settings of the classifier.
`java.lang.String` | `getRevision()` Returns the revision string.
`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 this classifier
`java.util.Enumeration<Option>` | `listOptions()` Returns an enumeration describing the available options.
`static void` | `main(java.lang.String[] argv)` Main method for testing this class.
`java.lang.String` | `multinomialWordTipText()` Returns the tip text for this property
`java.lang.String` | `numIterationsTipText()` Returns the tip text for this property
`void` | `setMultinomialWord(boolean val)` Sets whether use binary text representation
`void` | `setNumIterations(int numIterations)` Sets the number of iterations to be performed
`void` | `setOptions(java.lang.String[] options)` Parses a given list of options.
`java.lang.String` | `toString()` Returns a string representation of the classifier.
`void` | `updateClassifier(Instance instance)` Updates the classifier with the given instance.

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

### DMNBtext

    public DMNBtext()

Method Detail

### globalInfo

    public java.lang.String globalInfo()

  Returns a string describing this classifier

  Returns:
    a description of the classifier suitable for displaying in the explorer/experimenter gui

### getTechnicalInformation

    public 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.

  Specified by:
    `getTechnicalInformation` in interface `TechnicalInformationHandler`
  Returns:
    the technical information about this class

### getCapabilities

    public Capabilities getCapabilities()

  Returns default capabilities of the classifier.

  Specified by:
    `getCapabilities` in interface `CapabilitiesHandler`
  Overrides:
    `getCapabilities` in class `Classifier`
  Returns:
    the capabilities of this classifier
  See Also:
    `Capabilities`

### buildClassifier

    public void buildClassifier(Instances data)
                         throws java.lang.Exception

  Generates the classifier.

  Specified by:
    `buildClassifier` in class `Classifier`
  Parameters:
    `instances` - set of instances serving as training data
  Throws:
    `java.lang.Exception` - if the classifier has not been generated successfully

### updateClassifier

    public void updateClassifier(Instance instance)
                          throws java.lang.Exception

  Updates the classifier with the given instance.

  Specified by:
    `updateClassifier` in interface `UpdateableClassifier`
  Parameters:
    `instance` - the new training instance to include in the model
  Throws:
    `java.lang.Exception` - if the instance could not be incorporated in the model.

### distributionForInstance

    public double[] distributionForInstance(Instance instance)
                                     throws java.lang.Exception

  Calculates the class membership probabilities for the given test instance.

  Overrides:
    `distributionForInstance` in class `Classifier`
  Parameters:
    `instance` - the instance to be classified
  Returns:
    predicted class probability distribution
  Throws:
    `java.lang.Exception` - if there is a problem generating the prediction

### toString

    public java.lang.String toString()

  Returns a string representation of the classifier.

  Overrides:
    `toString` in class `java.lang.Object`
  Returns:
    a string representation of the classifier

### listOptions

    public java.util.Enumeration<Option> listOptions()

  Returns an enumeration describing the available options.

  Specified by:
    `listOptions` in interface `OptionHandler`
  Overrides:
    `listOptions` in class `Classifier`
  Returns:
    an enumeration of all the available options.

### setOptions

    public void setOptions(java.lang.String[] options)
                    throws java.lang.Exception

  Description copied from class: `Classifier`
  Parses a given list of options. Valid options are:

  -D
  If set, classifier is run in debug mode and may output additional info to the console.

  Specified by:
    `setOptions` in interface `OptionHandler`
  Overrides:
    `setOptions` in class `Classifier`
  Parameters:
    `options` - the list of options as an array of strings
  Throws:
    `java.lang.Exception` - if an option is not supported

### getOptions

    public java.lang.String[] getOptions()

  Gets the current settings of the classifier.

  Specified by:
    `getOptions` in interface `OptionHandler`
  Overrides:
    `getOptions` in class `Classifier`
  Returns:
    an array of strings suitable for passing to setOptions

### numIterationsTipText

    public java.lang.String numIterationsTipText()

  Returns the tip text for this property

  Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui

### setNumIterations

    public void setNumIterations(int numIterations)

  Sets the number of iterations to be performed

### getNumIterations

    public int getNumIterations()

  Gets the number of iterations to be performed

  Returns:
    the iterations to be performed

### multinomialWordTipText

    public java.lang.String multinomialWordTipText()

  Returns the tip text for this property

  Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui

### setMultinomialWord

    public void setMultinomialWord(boolean val)

  Sets whether use binary text representation

### getMultinomialWord

    public boolean getMultinomialWord()

  Gets whether use binary text representation

  Returns:
    whether use binary text representation

### getRevision

    public java.lang.String getRevision()

  Returns the revision string.

  Specified by:
    `getRevision` in interface `RevisionHandler`
  Overrides:
    `getRevision` in class `Classifier`
  Returns:
    the revision

### main

    public static void main(java.lang.String[] argv)

  Main method for testing this class.

  Parameters:
    `argv` - the options

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