weka.classifiers.rules.car

Class WeightedClassifier

java.lang.Object

weka.classifiers.AbstractClassifier

weka.classifiers.rules.car.CarClassifier

weka.classifiers.rules.car.WeightedClassifier

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

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

Class implemting three different weighted classifiers for class association rules. a) all rules are weighted equally with weight one (default behaviour). b) all rules are weighted linearly c) all rules are weighted using the inverse function 1/position in sort order of mining algorithm The pruning step is omitted. All mined rules are used for classifcation, if not specified otherwise with the -L option. 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.

-W weighting scheme
Sets the weighting scheme: inverse|linear|equal (default).

-L rule limit
Set a rule limit for the number of rules used for classification after the pruning step. Uses the first N rules only.

Version:

$Revision: 10209 $

Author:

Stefan Mutter

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
static weka.core.Tag[]	TAGS_SELECTION

Fields inherited from class weka.classifiers.AbstractClassifier

BATCH_SIZE_DEFAULT, NUM_DECIMAL_PLACES_DEFAULT

Constructor Summary

Constructors

Constructor and Description
WeightedClassifier()

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.
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
double	getMeasure(java.lang.String additionalMeasureName) Gets the additional statistics
java.lang.String[]	getOptions() Gets the current settings of the Classifier.
PruneCAR	getPrune() Gets the pruning algorithm: PrecedencePruning
java.lang.String	getRevision() Returns the revision string.
int	getRuleLimit() Gets the rule limit (-1 means no limit)
weka.core.SelectedTag	getWeightScheme() Gets the type of the weighting scheme
java.lang.String	globalInfo() Gets a description of WeightedClassifier
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	measureAverageRankCorrect() Gets the average rank of the first rule that covers an instance.
double	measureAverageRankFires() Gets the average rank of the first rule that covers an instance and predicts it correctly.
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	ruleLimitTipText() Gets the tipText for this option.
void	setCarMiner(weka.associations.CARuleMiner assoc) Sets the class association rule miner
void	setOptions(java.lang.String[] options) Parses a given list of options.
void	setRuleLimit(int n) Sets a rule limit.
void	setWeightScheme(weka.core.SelectedTag type) Sets the weighting scheme
java.lang.String	toString() Prints the rules
double	weight(java.lang.String type, double rank) Weights a rule
java.lang.String	weightSchemeTipText() Gets the tipText for this option.

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

sortAttributes

Methods inherited from class weka.classifiers.AbstractClassifier

batchSizeTipText, classifyInstance, 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

Field Detail

TAGS_SELECTION

public static final weka.core.Tag[] TAGS_SELECTION

Constructor Detail

WeightedClassifier

public WeightedClassifier()

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

globalInfo

public java.lang.String globalInfo()

Gets a description of WeightedClassifier

Returns:

a description of WeightedClassifier

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.

-W weighting scheme
Sets the weighting scheme: inverse|linear|equal (default).

-L rule limit
Set a rule limit for the number of rules used for classification after the pruning step. Uses the first N rules only.

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 PruneCAR getPrune()

Gets the pruning algorithm: PrecedencePruning

Returns:

the pruning algorithm

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

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

weightSchemeTipText

public java.lang.String weightSchemeTipText()

Gets the tipText for this option.

Returns:

the tipText for this option.

setWeightScheme

public void setWeightScheme(weka.core.SelectedTag type)

Sets the weighting scheme

Parameters:

type - the type of the weighting scheme: inverse | linear | equal

getWeightScheme

public weka.core.SelectedTag getWeightScheme()

Gets the type of the weighting scheme

Returns:

type of the weighting scheme: inverse | linear | equal

ruleLimitTipText

public java.lang.String ruleLimitTipText()

Gets the tipText for this option.

Returns:

the tipText for this option.

setRuleLimit

public void setRuleLimit(int n)

Sets a rule limit. Only the first n rules after pruning are then used for classification (-1 means no limit).

Parameters:

n - the rule limit

getRuleLimit

public int getRuleLimit()

Gets the rule limit (-1 means no limit)

Returns:

the rule limit

weight

public double weight(java.lang.String type,
                     double rank)

Weights a rule

Parameters:

type - the weighting scheme

rank - the rank of the rule in the sort order

Returns:

the weight of a rule

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

measureAverageRankFires

public double measureAverageRankFires()

Gets the average rank of the first rule that covers an instance and predicts it correctly.

Returns:

the average rank of the first rule that covers an instance and predicts it correctly.

measureAverageRankCorrect

public double measureAverageRankCorrect()

Gets the average rank of the first rule that covers an instance.

Returns:

the average rank of the first rule that covers an instance.

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