weka.associations.classification

Class CrTree

java.lang.Object

weka.associations.classification.PruneCAR

weka.associations.classification.CrTree

All Implemented Interfaces:

java.io.Serializable, weka.core.OptionHandler

Direct Known Subclasses:

JCBAPruning

public class CrTree
extends PruneCAR
implements java.io.Serializable

Class for building and using a CrTree. A CrTree(n-ary tree in child-sibling representation) can store classification association rules(CARs) and allows pruning and classification. Tree Structure described at: W. Li, J. Han, J.Pei: CMAR: Accurate and Efficient Classification Based on Multiple Class-Association Rules. In ICDM'01:369-376,2001. The child sibling representation for n-ary trees is used

Version:

$Revision: 10209 $

Author:

Stefan Mutter

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
CrTree() Constructor constructs an empty CrTree
CrTree(CrNode root, weka.core.Instances instances, weka.core.Instances onlyClass) Constructor
CrTree(weka.core.Instances instances, weka.core.Instances onlyClass) Constructor

Method Summary

Modifier and Type	Method and Description
void	deleteContent(CrNode node, int index) Deletes one rule out of the CrTree
void	deleteNode(CrNode node) deletes a node out of the CrTree if possible
CrList	getAssociateList() Gets the associated list
int	getDefaultClass() Gets the default class
java.lang.String[]	getOptions() Gets the current settings of the CrTree object.
CrNode	getRoot() Gets the root node
void	insertContent(CrNode node, weka.core.FastVector input) Adds another consequence to an existing premise.
void	insertNode(weka.core.FastVector rulePremise, weka.core.FastVector ruleConsequence) insert a new rule into the CrTree in three steps: 1.
boolean	isEmpty() Checks if the the CrTree is empty
java.util.Enumeration	listOptions() Returns an enumeration describing the available options.
void	makeEmpty() Deletes the whole CrTree and its associated list by setting the child pointer of the root to null
java.lang.String	pathToString(java.lang.String metricString) Prints a rule
void	preprocess(java.util.ArrayList<java.lang.Object> premises, java.util.ArrayList<java.lang.Object> consequences, java.util.ArrayList<java.lang.Object> confidences) The preprocessing step before a rule is inserted into a CrTree.
void	prune() Method for pruning a CrTree.
void	pruneBeforeInsertion(weka.core.FastVector premise, weka.core.FastVector consequence) Method that provides a pruning step before a rule is inserted into the CrTree.
int	prunedRules() Returns the number of pruned rules
weka.core.FastVector	pruningCriterions(weka.core.FastVector input) Potentially adds additional measures that can be used as pruning criterias to a rule.
void	removeAtChild(CrNode node, CrNode sibling) Deletes a node out of the parent list.
void	removeAtList(CrNode node) deletes the node out of the list that connects nodes storing the same item.
void	removeAtSibling(CrNode node) Deletes a node out of the child list.
int[]	reportSubtreeCount(CrNode subTreeRoot) Gets the class distribution of the rules from a subtree of a specified node
java.lang.String	rulePremise() Prints a rule premise (from bottom to top in the tree, respectively infrequent items to frequent ones).
weka.core.FastVector	search(weka.core.FastVector data) Searches for an existing rule premise are parts of an rule premise in the CrTree
void	setDefaultClass() Sets the default class as the amjority class in the instances.
void	setInstancesNoClass(weka.core.Instances instances) Sets the instances (without class attribute)
void	setInstancesOnlyClass(weka.core.Instances instances) Sets the class information
void	setOptions(java.lang.String[] options) Parses a given list of options.
weka.core.FastVector	sortItemSet(weka.associations.ItemSet current) Sorts an item set accoring to the frequencies values of the items.
java.lang.String	toString(java.lang.String metricString) Returns a string description of the CrTree Object
void	updateHeight(CrNode node) Adjust the (minimum) height of a CrListElement

Methods inherited from class weka.associations.classification.PruneCAR

forName

Methods inherited from class java.lang.Object

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

Methods inherited from interface weka.core.OptionHandler

makeCopy

Constructor Detail

CrTree

public CrTree()

Constructor constructs an empty CrTree

CrTree

public CrTree(CrNode root,
              weka.core.Instances instances,
              weka.core.Instances onlyClass)

Constructor

Parameters:

root - the root node

instances - the instances without class attribute

onlyClass - the class attribute and its values for all instances

CrTree

public CrTree(weka.core.Instances instances,
              weka.core.Instances onlyClass)

Constructor

Parameters:

instances - the instances without class attribute

onlyClass - the class attribute and its values for all instances

Method Detail

setInstancesNoClass

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

Sets the instances (without class attribute)

Specified by:

setInstancesNoClass in class PruneCAR

Parameters:

instances - instances without classattribute

setInstancesOnlyClass

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

Sets the class information

Specified by:

setInstancesOnlyClass in class PruneCAR

Parameters:

instances - the class attribute and its values

preprocess

public 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

The preprocessing step before a rule is inserted into a CrTree. The main purpose is to sort the items according to their frequencies in the datsaset. More frequent items will be found in nodes closer to the root.

Specified by:

preprocess in class PruneCAR

Parameters:

premises - the premises

consequences - the consequences

confidences - the interestingness measures

Throws:

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

setDefaultClass

public void setDefaultClass()

Sets the default class as the amjority class in the instances. The default class is stored in the head of the associated CrList.

getDefaultClass

public int getDefaultClass()

Gets the default class

Returns:

the default class coded as integer

sortItemSet

public final weka.core.FastVector sortItemSet(weka.associations.ItemSet current)

Sorts an item set accoring to the frequencies values of the items. For every item the resulting FastVector conatins two integer: attribute number and value

Parameters:

current - the item set

Returns:

a Fastvector with sorted attributes accoring to their frequencies.

pruningCriterions

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

Potentially adds additional measures that can be used as pruning criterias to a rule. This method is provided for the children of CrTree. This class implements no pruning and therefore needs no additional pruning criterias

Specified by:

pruningCriterions in class PruneCAR

Parameters:

input - pruning criteria

Returns:

a FastVector with the added criterias

pruneBeforeInsertion

public void pruneBeforeInsertion(weka.core.FastVector premise,
                                 weka.core.FastVector consequence)

Method that provides a pruning step before a rule is inserted into the CrTree. In its general form here, no pruning is done.

Specified by:

pruneBeforeInsertion in class PruneCAR

Parameters:

premise - the rule premise

consequence - the rule consequence

isEmpty

public final boolean isEmpty()

Checks if the the CrTree is empty

Specified by:

isEmpty in class PruneCAR

Returns:

true if it is empty, false otherwise

getRoot

public final CrNode getRoot()

Gets the root node

Returns:

the root node

getAssociateList

public final CrList getAssociateList()

Gets the associated list

Returns:

the associated list

removeAtSibling

public final void removeAtSibling(CrNode node)

Deletes a node out of the child list.

Parameters:

node - the node that has to be deletet out of the child list

removeAtChild

public final void removeAtChild(CrNode node,
                                CrNode sibling)

Deletes a node out of the parent list.

Parameters:

node - the node that has to be deleted

sibling - a sibling node

removeAtList

public final void removeAtList(CrNode node)

deletes the node out of the list that connects nodes storing the same item. If no other node stores the same item, the element in the associated list is deleted as well.

Parameters:

node - the node that has to be deleted

updateHeight

public final void updateHeight(CrNode node)

Adjust the (minimum) height of a CrListElement

Parameters:

node - the node that has to deleted

deleteContent

public final void deleteContent(CrNode node,
                                int index)

Deletes one rule out of the CrTree

Specified by:

deleteContent in class PruneCAR

Parameters:

node - the node where the consequence of the rule is stored

index - the index of the consequence

deleteNode

public final void deleteNode(CrNode node)

deletes a node out of the CrTree if possible

Parameters:

node - the node that should be deleted

insertContent

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

Adds another consequence to an existing premise.

Specified by:

insertContent in class PruneCAR

Parameters:

node - the node where the conesequence should be added

input - the consequence

insertNode

public final void insertNode(weka.core.FastVector rulePremise,
                             weka.core.FastVector ruleConsequence)

insert a new rule into the CrTree in three steps: 1. search for existing paths and the right node to start the insertion. 2. insert (rest of) premise 3. insert consequence and additional measures (by calling insertContent)

Parameters:

rulePremise - the rule premise

ruleConsequence - the consequence and additional measures

search

public final weka.core.FastVector search(weka.core.FastVector data)

Searches for an existing rule premise are parts of an rule premise in the CrTree

Parameters:

data - the rule premise

Returns:

the part of the rule premise that cannot be found in the CrTree

prune

public void prune()

Method for pruning a CrTree. In thgis general form of a CrTree there is no pruning involved. Children of this class implement this method with their pruning strategy.

Specified by:

prune in class PruneCAR

makeEmpty

public final void makeEmpty()

Deletes the whole CrTree and its associated list by setting the child pointer of the root to null

reportSubtreeCount

public int[] reportSubtreeCount(CrNode subTreeRoot)

Gets the class distribution of the rules from a subtree of a specified node

Parameters:

subTreeRoot - the root of the subtree

Returns:

the class distribution

rulePremise

public java.lang.String rulePremise()

Prints a rule premise (from bottom to top in the tree, respectively infrequent items to frequent ones).

Returns:

a string with a rule premise

toString

public java.lang.String toString(java.lang.String metricString)

Returns a string description of the CrTree Object

Specified by:

toString in class PruneCAR

Parameters:

metricString - the metric used

Returns:

a string describing the CrTree object

pathToString

public java.lang.String pathToString(java.lang.String metricString)

Prints a rule

Parameters:

metricString - the metric used for class association rule mining

Returns:

strting with rules with the same premise

getOptions

public java.lang.String[] getOptions()

Gets the current settings of the CrTree object. There are no options available.

Specified by:

getOptions in interface weka.core.OptionHandler

Returns:

an array with an empty string.

listOptions

public java.util.Enumeration listOptions()

Returns an enumeration describing the available options. There are no options available

Specified by:

listOptions in interface weka.core.OptionHandler

Returns:

a FastVector containing an empty string.

setOptions

public void setOptions(java.lang.String[] options)
                throws java.lang.Exception

Parses a given list of options. Valid options are:

There are no options available.

Specified by:

setOptions in interface weka.core.OptionHandler

Parameters:

options - the list of options as an array of strings

Throws:

java.lang.Exception - if an option is not supported

prunedRules

public int prunedRules()

Returns the number of pruned rules

Specified by:

prunedRules in class PruneCAR

Returns:

the number of pruned rules