MILR

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## weka.classifiers.mi
Class MILR

    java.lang.Object
      weka.classifiers.Classifier
          weka.classifiers.mi.MILR

All Implemented Interfaces:
  java.io.Serializable, java.lang.Cloneable, CapabilitiesHandler, MultiInstanceCapabilitiesHandler, OptionHandler, RevisionHandler

    public class MILR

extends Classifier
implements OptionHandler, MultiInstanceCapabilitiesHandler

Uses either standard or collective multi-instance assumption, but within linear regression. For the collective assumption, it offers arithmetic or geometric mean for the posteriors.

Valid options are:

     -D
      Turn on debugging output.

     -R <ridge>
      Set the ridge in the log-likelihood.

     -A [0|1|2]
      Defines the type of algorithm:
       0. standard MI assumption
       1. collective MI assumption, arithmetic mean for posteriors
       2. collective MI assumption, geometric mean for posteriors

Version:
  $Revision: 1.4 $
Author:
  Eibe Frank (eibe@cs.waikato.ac.nz), Xin Xu (xx5@cs.waikato.ac.nz)
See Also:
  Serialized Form

Field Summary
`static int` | `ALGORITHMTYPE_ARITHMETIC` collective MI assumption, arithmetic mean for posteriors
`static int` | `ALGORITHMTYPE_DEFAULT` standard MI assumption
`static int` | `ALGORITHMTYPE_GEOMETRIC` collective MI assumption, geometric mean for posteriors
`static Tag[]` | `TAGS_ALGORITHMTYPE` the types of algorithms

Constructor Summary
`MILR()`

Method Summary
`java.lang.String` | `algorithmTypeTipText()` Returns the tip text for this property
`void` | `buildClassifier(Instances train)` Builds the classifier
`double[]` | `distributionForInstance(Instance exmp)` Computes the distribution for a given exemplar
`SelectedTag` | `getAlgorithmType()` Gets the type of algorithm.
`Capabilities` | `getCapabilities()` Returns default capabilities of the classifier.
`Capabilities` | `getMultiInstanceCapabilities()` Returns the capabilities of this multi-instance classifier for the relational data.
`java.lang.String[]` | `getOptions()` Gets the current settings of the classifier.
`java.lang.String` | `getRevision()` Returns the revision string.
`double` | `getRidge()` Gets the ridge in the log-likelihood.
`java.lang.String` | `globalInfo()` Returns the tip text for this property
`java.util.Enumeration` | `listOptions()` Returns an enumeration describing the available options
`static void` | `main(java.lang.String[] argv)` Main method for testing this class.
`java.lang.String` | `ridgeTipText()` Returns the tip text for this property
`void` | `setAlgorithmType(SelectedTag newType)` Sets the algorithm type.
`void` | `setOptions(java.lang.String[] options)` Parses a given list of options.
`void` | `setRidge(double ridge)` Sets the ridge in the log-likelihood.
`java.lang.String` | `toString()` Gets a string describing the classifier.

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`

Field Detail

### ALGORITHMTYPE_DEFAULT

    public static final int ALGORITHMTYPE_DEFAULT

  standard MI assumption

  See Also:
    Constant Field Values

### ALGORITHMTYPE_ARITHMETIC

    public static final int ALGORITHMTYPE_ARITHMETIC

  collective MI assumption, arithmetic mean for posteriors

  See Also:
    Constant Field Values

### ALGORITHMTYPE_GEOMETRIC

    public static final int ALGORITHMTYPE_GEOMETRIC

  collective MI assumption, geometric mean for posteriors

  See Also:
    Constant Field Values

### TAGS_ALGORITHMTYPE

    public static final Tag[] TAGS_ALGORITHMTYPE

  the types of algorithms

Constructor Detail

### MILR

    public MILR()

Method Detail

### globalInfo

    public java.lang.String globalInfo()

  Returns the tip text for this property

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

### listOptions

    public java.util.Enumeration 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

  Parses a given list of options.

  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

### ridgeTipText

    public java.lang.String ridgeTipText()

  Returns the tip text for this property

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

### setRidge

    public void setRidge(double ridge)

  Sets the ridge in the log-likelihood.

  Parameters:
    `ridge` - the ridge

### getRidge

    public double getRidge()

  Gets the ridge in the log-likelihood.

  Returns:
    the ridge

### algorithmTypeTipText

    public java.lang.String algorithmTypeTipText()

  Returns the tip text for this property

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

### getAlgorithmType

    public SelectedTag getAlgorithmType()

  Gets the type of algorithm.

  Returns:
    the algorithm type

### setAlgorithmType

    public void setAlgorithmType(SelectedTag newType)

  Sets the algorithm type.

  Parameters:
    `newType` - the new algorithm type

### 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`

### getMultiInstanceCapabilities

    public Capabilities getMultiInstanceCapabilities()

  Returns the capabilities of this multi-instance classifier for the relational data.

  Specified by:
    `getMultiInstanceCapabilities` in interface `MultiInstanceCapabilitiesHandler`
  Returns:
    the capabilities of this object
  See Also:
    `Capabilities`

### buildClassifier

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

  Builds the classifier

  Specified by:
    `buildClassifier` in class `Classifier`
  Parameters:
    `train` - the training data to be used for generating the boosted classifier.
  Throws:
    `java.lang.Exception` - if the classifier could not be built successfully

### distributionForInstance

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

  Computes the distribution for a given exemplar

  Overrides:
    `distributionForInstance` in class `Classifier`
  Parameters:
    `exmp` - the exemplar for which distribution is computed
  Returns:
    the distribution
  Throws:
    `java.lang.Exception` - if the distribution can't be computed successfully

### toString

    public java.lang.String toString()

  Gets a string describing the classifier.

  Overrides:
    `toString` in class `java.lang.Object`
  Returns:
    a string describing the classifer built.

### getRevision

    public java.lang.String getRevision()

  Returns the revision string.

  Specified by:
    `getRevision` in interface `RevisionHandler`
  Returns:
    the revision

### main

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

  Main method for testing this class.

  Parameters:
    `argv` - should contain the command line arguments to the scheme (see Evaluation)

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