weka.associations.classification

Class PruneCAR

java.lang.Object

weka.associations.classification.PruneCAR

All Implemented Interfaces:

java.io.Serializable, weka.core.OptionHandler

Direct Known Subclasses:

CrTree

public abstract class PruneCAR
extends java.lang.Object
implements weka.core.OptionHandler, java.io.Serializable

Abstract scheme for storing and pruning class associations. All schemes for storing and pruning class associations implemement this class

Version:

$Revision: 10209 $

Author:

Stefan Mutter (mutter@cs.waikato.ac.nz)

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
PruneCAR()

Method Summary

Modifier and Type	Method and Description
abstract void	deleteContent(CrNode node, int index) Deletes a consequence from a node
static PruneCAR	forName(java.lang.String pruningName, java.lang.String[] options) Creates a new instance of a PruneCAR given it's class name and (optional) arguments to pass to it's setOptions method.
abstract void	insertContent(CrNode node, weka.core.FastVector input) Inserts a consequence and the according interestingness measures into a node
abstract boolean	isEmpty() Tests if there are rules
abstract void	preprocess(java.util.ArrayList<java.lang.Object> premises, java.util.ArrayList<java.lang.Object> consequences, java.util.ArrayList<java.lang.Object> confidences) Preprocesses rules before inserting them into the structure
abstract void	prune() Prunes rules out of tree
abstract void	pruneBeforeInsertion(weka.core.FastVector prem, weka.core.FastVector cons) Pruning step before a rule is inserted into the structure
abstract int	prunedRules() Gets the number of pruned rules.
abstract weka.core.FastVector	pruningCriterions(weka.core.FastVector input) FastVector defining additional pruning criteria
abstract void	setInstancesNoClass(weka.core.Instances instances) Sets the instances without the class attribute
abstract void	setInstancesOnlyClass(weka.core.Instances instances) Sets the instances where all attributes except for the class attribute are deleted
abstract java.lang.String	toString(java.lang.String metricType) Outputs the rules

Methods inherited from class java.lang.Object

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

Methods inherited from interface weka.core.OptionHandler

getOptions, listOptions, makeCopy, setOptions

Constructor Detail

PruneCAR

public PruneCAR()

Method Detail

isEmpty

public abstract boolean isEmpty()

Tests if there are rules

Returns:

true if there is no rule, false otherwise

setInstancesNoClass

public abstract void setInstancesNoClass(weka.core.Instances instances)

Sets the instances without the class attribute

Parameters:

instances - the instances

setInstancesOnlyClass

public abstract void setInstancesOnlyClass(weka.core.Instances instances)

Sets the instances where all attributes except for the class attribute are deleted

Parameters:

instances - the instances

preprocess

public abstract void preprocess(java.util.ArrayList<java.lang.Object> premises,
                                java.util.ArrayList<java.lang.Object> consequences,
                                java.util.ArrayList<java.lang.Object> confidences)
                         throws java.lang.Exception

Preprocesses rules before inserting them into the structure

Parameters:

premises - the premises

consequences - the consequences

confidences - the interestingness measures

Throws:

java.lang.Exception - throws eception if preprocessing is not possible

insertContent

public abstract void insertContent(CrNode node,
                                   weka.core.FastVector input)

Inserts a consequence and the according interestingness measures into a node

Parameters:

node - the node

input - the consequence and the interestingness measures

deleteContent

public abstract void deleteContent(CrNode node,
                                   int index)

Deletes a consequence from a node

Parameters:

node - the node

index - the index of the consequence

pruningCriterions

public abstract weka.core.FastVector pruningCriterions(weka.core.FastVector input)

FastVector defining additional pruning criteria

Parameters:

input - the criteria

Returns:

FastVector

pruneBeforeInsertion

public abstract void pruneBeforeInsertion(weka.core.FastVector prem,
                                          weka.core.FastVector cons)

Pruning step before a rule is inserted into the structure

Parameters:

prem - the premise

cons - the consequence

prune

public abstract void prune()

Prunes rules out of tree

prunedRules

public abstract int prunedRules()

Gets the number of pruned rules.

Returns:

the number of pruned rules

toString

public abstract java.lang.String toString(java.lang.String metricType)

Outputs the rules

Parameters:

metricType - the metrci type of the sort order

Returns:

a string

forName

public static PruneCAR forName(java.lang.String pruningName,
                               java.lang.String[] options)
                        throws java.lang.Exception

Creates a new instance of a PruneCAR given it's class name and (optional) arguments to pass to it's setOptions method. If the associator implements OptionHandler and the options parameter is non-null, the associator will have it's options set.

Parameters:

pruningName - the fully qualified class name of the PruneCAR

options - an array of options suitable for passing to setOptions. May be null.

Returns:

the newly created PruneCAR, ready for use.

Throws:

java.lang.Exception - if the PruneC>R name is invalid, or the options supplied are not acceptable to the PruneCAR