weka.classifiers.rules
Class OLM

java.lang.Object
  weka.classifiers.AbstractClassifier
      weka.classifiers.rules.OLM

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, Classifier, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler

public class OLM
extends AbstractClassifier
implements OptionHandler, TechnicalInformationHandler

This class is an implementation of the Ordinal Learning Method (OLM).
Further information regarding the algorithm and variants can be found in:

Arie Ben-David (1992). Automatic Generation of Symbolic Multiattribute Ordinal Knowledge-Based DSSs: methodology and Applications. Decision Sciences. 23:1357-1372.

BibTeX:

 @article{Ben-David1992,
    author = {Arie Ben-David},
    journal = {Decision Sciences},
    pages = {1357-1372},
    title = {Automatic Generation of Symbolic Multiattribute Ordinal Knowledge-Based DSSs: methodology and Applications},
    volume = {23},
    year = {1992}
 }
 

Valid options are:

 -R <integer>
  The resolution mode. Valid values are:
  0 for conservative resolution, 1 for random resolution, 2 for average, and 3 for no resolution. (default 0).

 -C <integer>
  The classification mode. Valid values are:
  0 for conservative classification, 1 for nearest neighbour classification. (default 0).

 -U <size>
  SSet maximum size of rule base
  (default: -U <number of examples>)

Version:

$Revision: 5928 $

Author:

TriDat Tran

See Also:

Serialized Form

Field Summary

static int	CLASSIFICATION_CONSERVATIVE
static int	CLASSIFICATION_NEARESTNEIGHBOUR
static int	RESOLUTION_AVERAGE
static int	RESOLUTION_CONSERVATIVE
static int	RESOLUTION_NONE
static int	RESOLUTION_RANDOM
static Tag[]	TAGS_CLASSIFICATION
static Tag[]	TAGS_RESOLUTION

Constructor Summary

OLM()

Method Summary

void	buildClassifier(Instances data) Generates the classifier.
java.lang.String	classificationModeTipText() Returns the tip text for this property
double	classifyInstance(Instance inst) Classifies a given instance.
Capabilities	getCapabilities() Returns default capabilities of the classifier.
SelectedTag	getClassificationMode() Gets the classification mode.
java.lang.String[]	getOptions() Gets the current settings of the Classifier.
SelectedTag	getResolutionMode() Gets the resolution mode.
java.lang.String	getRevision() Returns the revision string.
int	getRuleSize()
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 the classifier.
java.util.Enumeration	listOptions() Returns an enumeration describing the available options Valid options are:
static void	main(java.lang.String[] args) Main method for testing this class
java.lang.String	resolutionModeTipText() Returns the tip text for this property
java.lang.String	ruleSizeTipText() Returns the tip text for this property
void	setClassificationMode(SelectedTag newMethod) Sets the classification mode.
void	setOptions(java.lang.String[] options) Parses a given list of options.
void	setResolutionMode(SelectedTag newMethod) Sets the resolution mode.
void	setRuleSize(int s)
java.lang.String	toString() Prints a description of the classifier.

Methods inherited from class weka.classifiers.AbstractClassifier

debugTipText, distributionForInstance, forName, getDebug, makeCopies, makeCopy, setDebug

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

RESOLUTION_NONE

public static final int RESOLUTION_NONE

See Also:

Constant Field Values

RESOLUTION_AVERAGE

public static final int RESOLUTION_AVERAGE

See Also:

Constant Field Values

RESOLUTION_RANDOM

public static final int RESOLUTION_RANDOM

See Also:

Constant Field Values

RESOLUTION_CONSERVATIVE

public static final int RESOLUTION_CONSERVATIVE

See Also:

Constant Field Values

TAGS_RESOLUTION

public static final Tag[] TAGS_RESOLUTION

CLASSIFICATION_CONSERVATIVE

public static final int CLASSIFICATION_CONSERVATIVE

See Also:

Constant Field Values

CLASSIFICATION_NEARESTNEIGHBOUR

public static final int CLASSIFICATION_NEARESTNEIGHBOUR

See Also:

Constant Field Values

TAGS_CLASSIFICATION

public static final Tag[] TAGS_CLASSIFICATION

Constructor Detail

OLM

public OLM()

Method Detail

getCapabilities

public Capabilities getCapabilities()

Returns default capabilities of the classifier.

Specified by:

getCapabilities in interface Classifier

Specified by:

getCapabilities in interface CapabilitiesHandler

Overrides:

getCapabilities in class AbstractClassifier

Returns:

the capabilities of this classifier

See Also:

Capabilities

globalInfo

public java.lang.String globalInfo()

Returns a string describing the classifier.

Returns:

a description 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

classifyInstance

public double classifyInstance(Instance inst)

Classifies a given instance.

Specified by:

classifyInstance in interface Classifier

Overrides:

classifyInstance in class AbstractClassifier

Parameters:

inst - the instance to be classified

Returns:

the classification

listOptions

public java.util.Enumeration listOptions()

Returns an enumeration describing the available options Valid options are:

Specified by:

listOptions in interface OptionHandler

Overrides:

listOptions in class AbstractClassifier

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. Valid options are:

 -R <integer>
  The resolution mode. Valid values are:
  0 for conservative resolution, 1 for random resolution, 2 for average, and 3 for no resolution. (default 0).

 -C <integer>
  The classification mode. Valid values are:
  0 for conservative classification, 1 for nearest neighbour classification. (default 0).

 -U <size>
  SSet maximum size of rule base
  (default: -U <number of examples>)

Specified by:

setOptions in interface OptionHandler

Overrides:

setOptions in class AbstractClassifier

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 AbstractClassifier

Returns:

an array of strings suitable for passing to setOptions

resolutionModeTipText

public java.lang.String resolutionModeTipText()

Returns the tip text for this property

Returns:

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

setResolutionMode

public void setResolutionMode(SelectedTag newMethod)

Sets the resolution mode.

Parameters:

newMethod - the new evaluation mode.

getResolutionMode

public SelectedTag getResolutionMode()

Gets the resolution mode.

Returns:

the evaluation mode.

setClassificationMode

public void setClassificationMode(SelectedTag newMethod)

Sets the classification mode.

Parameters:

newMethod - the new classification mode.

getClassificationMode

public SelectedTag getClassificationMode()

Gets the classification mode.

Returns:

the classiciation mode

classificationModeTipText

public java.lang.String classificationModeTipText()

Returns the tip text for this property

Returns:

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

ruleSizeTipText

public java.lang.String ruleSizeTipText()

Returns the tip text for this property

Returns:

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

getRuleSize

public int getRuleSize()

setRuleSize

public void setRuleSize(int s)

buildClassifier

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

Generates the classifier.

Specified by:

buildClassifier in interface Classifier

Parameters:

data - the data to be used

Throws:

java.lang.Exception - if the classifier can't built successfully

toString

public java.lang.String toString()

Prints a description of the classifier.

Overrides:

toString in class java.lang.Object

Returns:

a description of the classifier as a string

getRevision

public java.lang.String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class AbstractClassifier

Returns:

the revision

main

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

Main method for testing this class