MDD (weka-stable 3.6.8 API)

java.lang.Object
- weka.classifiers.Classifier
- - weka.classifiers.mi.MDD

All Implemented Interfaces:: Serializable, Cloneable, CapabilitiesHandler, MultiInstanceCapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler

public class MDD
extends Classifier
implements OptionHandler, MultiInstanceCapabilitiesHandler, TechnicalInformationHandler

Modified Diverse Density algorithm, with collective assumption.

More information about DD:

Oded Maron (1998). Learning from ambiguity.

O. Maron, T. Lozano-Perez (1998). A Framework for Multiple Instance Learning. Neural Information Processing Systems. 10.

BibTeX:

 @phdthesis{Maron1998,
    author = {Oded Maron},
    school = {Massachusetts Institute of Technology},
    title = {Learning from ambiguity},
    year = {1998}
 }
 
 @article{Maron1998,
    author = {O. Maron and T. Lozano-Perez},
    journal = {Neural Information Processing Systems},
    title = {A Framework for Multiple Instance Learning},
    volume = {10},
    year = {1998}
 }

Valid options are:

 -D
  Turn on debugging output.

 -N <num>
  Whether to 0=normalize/1=standardize/2=neither.
  (default 1=standardize)

Version:: $Revision: 5545 $
Author:: Eibe Frank (eibe@cs.waikato.ac.nz), Xin Xu (xx5@cs.waikato.ac.nz)
See Also:: Serialized Form

Field Summary

Fields
Modifier and Type	Field and Description
`static int`	`FILTER_NONE` No normalization/standardization
`static int`	`FILTER_NORMALIZE` Normalize training data
`static int`	`FILTER_STANDARDIZE` Standardize training data
`protected Instances`	`m_Attributes` All attribute names
`protected int[]`	`m_Classes` Class labels for each bag
`protected int`	`m_ClassIndex` The index of the class attribute
`protected double[][][]`	`m_Data` MI data
`protected Filter`	`m_Filter` The filter used to standardize/normalize all values.
`protected int`	`m_filterType` Whether to normalize/standardize/neither, default:standardize
`protected ReplaceMissingValues`	`m_Missing` The filter used to get rid of missing values.
`protected int`	`m_NumClasses` The number of the class labels
`protected double[]`	`m_Par`
`static Tag[]`	`TAGS_FILTER` The filter to apply to the training data

Fields inherited from class weka.classifiers.Classifier
m_Debug

Constructor Summary

Constructors
Constructor and Description

MDD()

Constructors
Constructor and Description
`MDD()`

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`buildClassifier(Instances train)` Builds the classifier
`double[]`	`distributionForInstance(Instance exmp)` Computes the distribution for a given exemplar
`String`	`filterTypeTipText()` Returns the tip text for this property
`Capabilities`	`getCapabilities()` Returns default capabilities of the classifier.
`SelectedTag`	`getFilterType()` Gets how the training data will be transformed.
`Capabilities`	`getMultiInstanceCapabilities()` Returns the capabilities of this multi-instance classifier for the relational data.
`String[]`	`getOptions()` Gets the current settings of the classifier.
`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.
`String`	`globalInfo()` Returns a string describing this filter
`Enumeration`	`listOptions()` Returns an enumeration describing the available options
`static void`	`main(String[] argv)` Main method for testing this class.
`void`	`setFilterType(SelectedTag newType)` Sets how the training data will be transformed.
`void`	`setOptions(String[] options)` Parses a given list of options.
`String`	`toString()` Gets a string describing the classifier.

Methods inherited from class weka.classifiers.Classifier
classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, runClassifier, setDebug

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

- Field Detail
  - m_ClassIndex
```
protected int m_ClassIndex
```
    The index of the class attribute
  - m_Par
```
protected double[] m_Par
```
  - m_NumClasses
```
protected int m_NumClasses
```
    The number of the class labels
  - m_Classes
```
protected int[] m_Classes
```
    Class labels for each bag
  - m_Data
```
protected double[][][] m_Data
```
    MI data
  - m_Attributes
```
protected Instances m_Attributes
```
    All attribute names
  - m_Filter
```
protected Filter m_Filter
```
    The filter used to standardize/normalize all values.
  - m_filterType
```
protected int m_filterType
```
    Whether to normalize/standardize/neither, default:standardize
  - FILTER_NORMALIZE
```
public static final int FILTER_NORMALIZE
```
    Normalize training data
    
    See Also:
    
    Constant Field Values
  - FILTER_STANDARDIZE
```
public static final int FILTER_STANDARDIZE
```
    Standardize training data
    
    See Also:
    
    Constant Field Values
  - FILTER_NONE
```
public static final int FILTER_NONE
```
    No normalization/standardization
    
    See Also:
    
    Constant Field Values
  - TAGS_FILTER
```
public static final Tag[] TAGS_FILTER
```
    The filter to apply to the training data
  - m_Missing
```
protected ReplaceMissingValues m_Missing
```
    The filter used to get rid of missing values.
- Constructor Detail
  - MDD
```
public MDD()
```
- Method Detail
  - globalInfo
```
public String globalInfo()
```
    Returns a string describing this filter
    
    Returns:
    
    a description of the filter 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
  - listOptions
```
public 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(String[] options)
                throws 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:
    
    Exception - if an option is not supported
  - getOptions
```
public 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
  - filterTypeTipText
```
public String filterTypeTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getFilterType
```
public SelectedTag getFilterType()
```
    Gets how the training data will be transformed. Will be one of FILTER_NORMALIZE, FILTER_STANDARDIZE, FILTER_NONE.
    
    Returns:
    
    the filtering mode
  - setFilterType
```
public void setFilterType(SelectedTag newType)
```
    Sets how the training data will be transformed. Should be one of FILTER_NORMALIZE, FILTER_STANDARDIZE, FILTER_NONE.
    
    Parameters:
    
    newType - the new filtering mode
  - 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 Exception
```
    Builds the classifier
    
    Specified by:
    
    buildClassifier in class Classifier
    
    Parameters:
    
    train - the training data to be used for generating the boosted classifier.
    
    Throws:
    
    Exception - if the classifier could not be built successfully
  - distributionForInstance
```
public double[] distributionForInstance(Instance exmp)
                                 throws 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:
    
    Exception - if the distribution can't be computed successfully
  - toString
```
public String toString()
```
    Gets a string describing the classifier.
    
    Overrides:
    
    toString in class Object
    
    Returns:
    
    a string describing the classifer built.
  - getRevision
```
public 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(String[] argv)
```
    Main method for testing this class.
    
    Parameters:
    
    argv - should contain the command line arguments to the scheme (see Evaluation)

Class MDD

Field Summary

Fields inherited from class weka.classifiers.Classifier

Constructor Summary

Method Summary

Methods inherited from class weka.classifiers.Classifier

Methods inherited from class java.lang.Object

Field Detail

m_ClassIndex

m_Par

m_NumClasses

m_Classes

m_Data

m_Attributes

m_Filter

m_filterType

FILTER_NORMALIZE

FILTER_STANDARDIZE

FILTER_NONE

TAGS_FILTER

m_Missing

Constructor Detail

MDD

Method Detail

globalInfo

getTechnicalInformation

listOptions

setOptions

getOptions

filterTypeTipText

getFilterType

setFilterType

getCapabilities

getMultiInstanceCapabilities

buildClassifier

distributionForInstance

toString

getRevision

main