weka.classifiers.rules.car

Class JCBA

java.lang.Object

weka.classifiers.AbstractClassifier

weka.classifiers.rules.car.CarClassifier

weka.classifiers.rules.car.JCBA

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, weka.classifiers.Classifier, weka.core.AdditionalMeasureProducer, weka.core.BatchPredictor, weka.core.CapabilitiesHandler, weka.core.CapabilitiesIgnorer, weka.core.CommandlineRunnable, weka.core.OptionHandler, weka.core.RevisionHandler, weka.core.TechnicalInformationHandler

public class JCBA
extends CarClassifier
implements weka.core.OptionHandler, weka.core.AdditionalMeasureProducer, weka.core.CapabilitiesHandler, weka.core.TechnicalInformationHandler

Class implemting a java version of the CBA algorithm using a CrTree. Alternatively the classifier can be used as a standard decision list classifier. The Tree Structure is described in: W. Li, J. Han, J.Pei: CMAR: Accurate and Efficient Classification Based on Multiple Class-Association Rules. In ICDM'01:369-376,2001. The CBA algorithm is described in: B. Liu, W. Hsu, Y. Ma: Integrating Classification and Association Rule Mining. In KDD'98:80-86,1998. Valid options are:

-A Class Association Rule Miner String
Class Association Rule Miner String should contain the full class name of a scheme included for selection followed by options to the Class Association Rule Miner.

-C confidence value
Sets the confidence value for the optional pessimistic-error-rate-based pruning (default 0.25).

-E
If set the optional pessimistic-error-rate-based pruning is enabled.

-N
If set the optional and the obligatory pruning step are disabled. Classifier behaves like a standard decision list classifier.

-V
If set the mined rule set is printed out as well.

Version:

$Revision: 10209 $

Author:

Stefan Mutter

See Also:

Serialized Form

Field Summary

Fields inherited from class weka.classifiers.AbstractClassifier

BATCH_SIZE_DEFAULT, NUM_DECIMAL_PLACES_DEFAULT

Constructor Summary

Constructors

Constructor and Description
JCBA()

Method Summary

Modifier and Type	Method and Description
void	buildClassifier(weka.core.Instances newInstances) Generates the classifier.
java.lang.String	carMinerTipText() Gets the tipText for this option.
java.lang.String	CBATipText() Gets the tipText for the specified option.
java.lang.String	CFTipText() Gets the tipText for the specified option.
double	classifyInstance(weka.core.Instance instance) Classifies an instance
double[]	distributionForInstance(weka.core.Instance newInstance) Returns the class distribution for an instance
java.util.Enumeration	enumerateMeasures() Lists all additional statistics that are available
weka.core.Capabilities	getCapabilities() Returns default capabilities of the base associator.
weka.associations.CARuleMiner	getCarMiner() Gets the class association rule miner
boolean	getCBA() Gets whether or not CBA or a standard decision list classifier is used
float	getCF() Gets the confidence value for pessimistic-error-rate-based pruning
double	getMeasure(java.lang.String additionalMeasureName) Gets the additional statistics
java.lang.String[]	getOptions() Gets the current settings of the Classifier.
boolean	getOptPruning() Gets whether or not optional pruning is turned on
JCBAPruning	getPrune() Gets the pruning algorithm: JCBAPruning
java.lang.String	getRevision() Returns the revision string.
weka.core.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.
boolean	getTreeOutput() Gets whether or not the mined rule set is part of the output
java.lang.String	globalInfo() Gets a description of the JCBA algorithm
double	intermediateClassificationForInstance(weka.core.Instance instance, JCBAPruning tree, weka.core.Instances instances) Does the intermediate classification step during the CBA's obligatory pruning
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	measureMiningTime() Gets the mining time
double	measureNumClassRules() Gets the number of rules used for classification
double	measureNumMinedRules() Gets the number of mined rules
double	measureNumPrunedRules() Gets the number of rules after the optional pruning step
double	measurePruningTime() Gets the pruning time in seconds
java.lang.String	optPruningTipText() Gets the tipText for the specified option.
void	setCarMiner(weka.associations.CARuleMiner assoc) Sets the class association rule miner
void	setCBA(boolean flag) Sets whether or not CBA or a standard decision list classifier is used
void	setCF(float value) Sets the confidence value for pessimistic-error-rate-based pruning
void	setOptions(java.lang.String[] options) Parses a given list of options.
void	setOptPruning(boolean flag) Sets optional pruning
void	setTreeOutput(boolean flag) Sets whether or not mined rule set is part of the output
java.lang.String	toString() Prints the rules
java.lang.String	treeOutputTipText() Gets the tipText for the specified option.

Methods inherited from class weka.classifiers.rules.car.CarClassifier

sortAttributes

Methods inherited from class weka.classifiers.AbstractClassifier

batchSizeTipText, debugTipText, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, postExecution, preExecution, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlaces

Methods inherited from class java.lang.Object

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

Methods inherited from interface weka.core.OptionHandler

makeCopy

Constructor Detail

JCBA

public JCBA()

Method Detail

getCapabilities

public weka.core.Capabilities getCapabilities()

Returns default capabilities of the base associator.

Specified by:

getCapabilities in interface weka.classifiers.Classifier

Specified by:

getCapabilities in interface weka.core.CapabilitiesHandler

Overrides:

getCapabilities in class weka.classifiers.AbstractClassifier

Returns:

the capabilities of the base classifier

getTechnicalInformation

public weka.core.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 weka.core.TechnicalInformationHandler

Returns:

the technical information about this class

globalInfo

public java.lang.String globalInfo()

Gets a description of the JCBA algorithm

Returns:

a description of the JCBA algorithm

listOptions

public java.util.Enumeration listOptions()

Returns an enumeration describing the available options

Specified by:

listOptions in interface weka.core.OptionHandler

Overrides:

listOptions in class weka.classifiers.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:

-A Class Association Rule Miner String
Class Association Rule Miner String should contain the full class name of a scheme included for selection followed by options to the Class Association Rule Miner.

-C confidence value
Sets the confidence value for the optional pessimistic-error-rate-based pruning (default 0.25). -E
If set the optional pessimistic-error-rate-based pruning is enabled.

-N
If set the optional and the obligatory pruning step are disabled. Classifier behaves like a standard decision list classifier.

-V
If set the mined rule set is printed out as well.

Specified by:

setOptions in interface weka.core.OptionHandler

Overrides:

setOptions in class weka.classifiers.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 weka.core.OptionHandler

Overrides:

getOptions in class weka.classifiers.AbstractClassifier

Returns:

an array of strings suitable for passing to setOptions

carMinerTipText

public java.lang.String carMinerTipText()

Gets the tipText for this option.

Returns:

the tipText for this option.

setCarMiner

public void setCarMiner(weka.associations.CARuleMiner assoc)

Sets the class association rule miner

Parameters:

assoc - the class association rule miner

getCarMiner

public weka.associations.CARuleMiner getCarMiner()

Gets the class association rule miner

Returns:

the class association rule miner

getPrune

public JCBAPruning getPrune()

Gets the pruning algorithm: JCBAPruning

Returns:

the pruning algorithm

optPruningTipText

public java.lang.String optPruningTipText()

Gets the tipText for the specified option.

Returns:

the tipText for the specified option.

setOptPruning

public void setOptPruning(boolean flag)

Sets optional pruning

Parameters:

flag - boolean flag

getOptPruning

public boolean getOptPruning()

Gets whether or not optional pruning is turned on

Returns:

true if optional pruning is turned on, false otherwise.

CFTipText

public java.lang.String CFTipText()

Gets the tipText for the specified option.

Returns:

the tipText for the specified option.

setCF

public void setCF(float value)

Sets the confidence value for pessimistic-error-rate-based pruning

Parameters:

value - the confidence value

getCF

public float getCF()

Gets the confidence value for pessimistic-error-rate-based pruning

Returns:

the confidence value

treeOutputTipText

public java.lang.String treeOutputTipText()

Gets the tipText for the specified option.

Returns:

the tipText for the specified option.

setTreeOutput

public void setTreeOutput(boolean flag)

Sets whether or not mined rule set is part of the output

Parameters:

flag - boolean flag

getTreeOutput

public boolean getTreeOutput()

Gets whether or not the mined rule set is part of the output

Returns:

true if mined rule set is part of the output, false otherwise

CBATipText

public java.lang.String CBATipText()

Gets the tipText for the specified option.

Returns:

the tipText for the specified option.

setCBA

public void setCBA(boolean flag)

Sets whether or not CBA or a standard decision list classifier is used

Parameters:

flag - true if CBA is used, false otherwise

getCBA

public boolean getCBA()

Gets whether or not CBA or a standard decision list classifier is used

Returns:

true if CBA is used, false otherwise

buildClassifier

public void buildClassifier(weka.core.Instances newInstances)
                     throws java.lang.Exception

Generates the classifier.

Specified by:

buildClassifier in interface weka.classifiers.Classifier

Parameters:

newInstances - set of instances serving as training data

Throws:

java.lang.Exception - if the classifier has not been generated successfully

classifyInstance

public double classifyInstance(weka.core.Instance instance)
                        throws java.lang.Exception

Classifies an instance

Specified by:

classifyInstance in interface weka.classifiers.Classifier

Overrides:

classifyInstance in class weka.classifiers.AbstractClassifier

Parameters:

instance - the instance

Returns:

the predicted class

Throws:

java.lang.Exception - exception if instance cannot be classified

distributionForInstance

public double[] distributionForInstance(weka.core.Instance newInstance)
                                 throws java.lang.Exception

Returns the class distribution for an instance

Specified by:

distributionForInstance in interface weka.classifiers.Classifier

Overrides:

distributionForInstance in class weka.classifiers.AbstractClassifier

Parameters:

newInstance - the instance

Returns:

the class distribution

Throws:

java.lang.Exception - exception if it cannot be calculated

intermediateClassificationForInstance

public double intermediateClassificationForInstance(weka.core.Instance instance,
                                                    JCBAPruning tree,
                                                    weka.core.Instances instances)
                                             throws java.lang.Exception

Does the intermediate classification step during the CBA's obligatory pruning

Parameters:

instance - the instance to classifiy

tree - the actual CrTree with the actual rule set

instances - the instances

Returns:

the predicted class label

Throws:

java.lang.Exception - exception if instance cannot be classified

toString

public java.lang.String toString()

Prints the rules

Overrides:

toString in class java.lang.Object

Returns:

the rules

enumerateMeasures

public java.util.Enumeration enumerateMeasures()

Lists all additional statistics that are available

Specified by:

enumerateMeasures in interface weka.core.AdditionalMeasureProducer

Returns:

list of the names of the additional measures

getMeasure

public double getMeasure(java.lang.String additionalMeasureName)

Gets the additional statistics

Specified by:

getMeasure in interface weka.core.AdditionalMeasureProducer

Parameters:

additionalMeasureName - the name of the additional measure

Returns:

the value of the measure

measureMiningTime

public double measureMiningTime()

Gets the mining time

Returns:

the mining time in seconds

measurePruningTime

public double measurePruningTime()

Gets the pruning time in seconds

Returns:

the pruning time in seconds

measureNumMinedRules

public double measureNumMinedRules()

Gets the number of mined rules

Returns:

the number of mined rules

measureNumPrunedRules

public double measureNumPrunedRules()

Gets the number of rules after the optional pruning step

Returns:

the number of rules after the optional pruning step

measureNumClassRules

public double measureNumClassRules()

Gets the number of rules used for classification

Returns:

the number of rules used for classification

getRevision

public java.lang.String getRevision()

Returns the revision string.

Specified by:

getRevision in interface weka.core.RevisionHandler

Overrides:

getRevision in class weka.classifiers.AbstractClassifier

Returns:

the revision

main

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

Main method for testing this class.

Parameters:

argv - the options