weka.associations

Class GeneralizedSequentialPatterns

java.lang.Object

weka.associations.AbstractAssociator

weka.associations.GeneralizedSequentialPatterns

All Implemented Interfaces:

Serializable, Cloneable, Associator, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler

public class GeneralizedSequentialPatterns
extends AbstractAssociator
implements OptionHandler, TechnicalInformationHandler

Class implementing a GSP algorithm for discovering sequential patterns in a sequential data set.
The attribute identifying the distinct data sequences contained in the set can be determined by the respective option. Furthermore, the set of output results can be restricted by specifying one or more attributes that have to be contained in each element/itemset of a sequence.

For further information see:

Ramakrishnan Srikant, Rakesh Agrawal (1996). Mining Sequential Patterns: Generalizations and Performance Improvements.

BibTeX:

 @proceedings{Srikant1996,
    author = {Ramakrishnan Srikant and Rakesh Agrawal},
    booktitle = {Advances in Database Technology EDBT '96},
    publisher = {Springer},
    title = {Mining Sequential Patterns: Generalizations and Performance Improvements},
    year = {1996}
 }
 

Valid options are:

 -D
  If set, algorithm is run in debug mode and
  may output additional info to the console

 -S <minimum support threshold>
  The miminum support threshold.
  (default: 0.9)

 -I <attribute number representing the data sequence ID
  The attribute number representing the data sequence ID.
  (default: 0)

 -F <attribute numbers used for result filtering
  The attribute numbers used for result filtering.
  (default: -1)

Version:

$Revision: 5504 $

Author:

Sebastian Beer

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
GeneralizedSequentialPatterns() Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
void	buildAssociations(Instances data) Extracts all sequential patterns out of a given sequential data set and prints out the results.
String	dataSeqIDTipText() Returns the dataSeqID option tip text for the Weka GUI.
String	debugTipText() Returns the tip text for this property
void	extractFilterAttributes(String attrNumbers) Parses a given String containing attribute numbers which are used for result filtering.
String	filterAttributesTipText() Returns the filterAttributes option tip text for the Weka GUI.
String	getAlgorithmStart() Returns the time/date string the algorithm was started
Capabilities	getCapabilities() Returns the Capabilities of the algorithm.
String	getCycleEnd() Returns the time/date string the cycle ended
String	getCycleStart() Returns the time/date string the cycle was started
int	getDataSeqID() Returns the attribute representing the data sequence ID.
boolean	getDebug() Get whether debugging is turned on.
String	getFilterAttributes() Returns the String containing the attributes which are used for output filtering.
double	getMinSupport() Returns the minimum support threshold.
String[]	getOptions() Returns an Array containing the current options settings.
String	getRevision() Returns the revision string.
TechnicalInformation	getTechnicalInformation() Returns TechnicalInformation about the paper related to the algorithm.
String	globalInfo() Returns global information about the algorithm.
Enumeration	listOptions() Returns an enumeration of the available options.
static void	main(String[] args) Main method.
String	minSupportTipText() Returns the minimum support option tip text for the Weka GUI.
void	setDataSeqID(int value) Sets the attribute representing the data sequence ID.
void	setDebug(boolean value) Set debugging mode.
void	setFilterAttributes(String value) Sets the String containing the attributes which are used for output filtering.
void	setMinSupport(double value) Sets the minimum support threshold.
void	setOptions(String[] options) Parses a given list of options.
String	toString() Returns a String containing the result information of the algorithm.

Methods inherited from class weka.associations.AbstractAssociator

forName, makeCopies, makeCopy

Methods inherited from class java.lang.Object

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

Constructor Detail

GeneralizedSequentialPatterns

public GeneralizedSequentialPatterns()

Constructor.

Method Detail

globalInfo

public String globalInfo()

Returns global information about the algorithm.

Returns:

the global information

getTechnicalInformation

public TechnicalInformation getTechnicalInformation()

Returns TechnicalInformation about the paper related to the algorithm.

Specified by:

getTechnicalInformation in interface TechnicalInformationHandler

Returns:

the TechnicalInformation

listOptions

public Enumeration listOptions()

Returns an enumeration of the available options.

Specified by:

listOptions in interface OptionHandler

Returns:

the available options

setOptions

public void setOptions(String[] options)
                throws Exception

Parses a given list of options.

Valid options are:

 -D
  If set, algorithm is run in debug mode and
  may output additional info to the console

 -S <minimum support threshold>
  The miminum support threshold.
  (default: 0.9)

 -I <attribute number representing the data sequence ID
  The attribute number representing the data sequence ID.
  (default: 0)

 -F <attribute numbers used for result filtering
  The attribute numbers used for result filtering.
  (default: -1)

Specified by:

setOptions in interface OptionHandler

Parameters:

options - the Array containing the options

Throws:

Exception - if an option is not supported

getOptions

public String[] getOptions()

Returns an Array containing the current options settings.

Specified by:

getOptions in interface OptionHandler

Returns:

the Array containing the settings

getCapabilities

public Capabilities getCapabilities()

Returns the Capabilities of the algorithm.

Specified by:

getCapabilities in interface Associator

Specified by:

getCapabilities in interface CapabilitiesHandler

Overrides:

getCapabilities in class AbstractAssociator

Returns:

the Capabilities

See Also:

Capabilities

buildAssociations

public void buildAssociations(Instances data)
                       throws Exception

Extracts all sequential patterns out of a given sequential data set and prints out the results.

Specified by:

buildAssociations in interface Associator

Parameters:

data - the original data set

Throws:

Exception - if the associator has not been generated successfully

extractFilterAttributes

public void extractFilterAttributes(String attrNumbers)

Parses a given String containing attribute numbers which are used for result filtering.

Parameters:

attrNumbers - the String of attribute numbers

dataSeqIDTipText

public String dataSeqIDTipText()

Returns the dataSeqID option tip text for the Weka GUI.

Returns:

the option tip text

getDataSeqID

public int getDataSeqID()

Returns the attribute representing the data sequence ID.

Returns:

the data sequence ID

setDataSeqID

public void setDataSeqID(int value)

Sets the attribute representing the data sequence ID.

Parameters:

value - the data sequence ID to set

filterAttributesTipText

public String filterAttributesTipText()

Returns the filterAttributes option tip text for the Weka GUI.

Returns:

the option tip text

getFilterAttributes

public String getFilterAttributes()

Returns the String containing the attributes which are used for output filtering.

Returns:

the String containing the attributes

setFilterAttributes

public void setFilterAttributes(String value)

Sets the String containing the attributes which are used for output filtering.

Parameters:

value - the String containing the attributes

minSupportTipText

public String minSupportTipText()

Returns the minimum support option tip text for the Weka GUI.

Returns:

the option tip text

getMinSupport

public double getMinSupport()

Returns the minimum support threshold.

Returns:

the minimum support threshold

setMinSupport

public void setMinSupport(double value)

Sets the minimum support threshold.

Parameters:

value - the minimum support threshold

setDebug

public void setDebug(boolean value)

Set debugging mode.

Parameters:

value - true if debug output should be printed

getDebug

public boolean getDebug()

Get whether debugging is turned on.

Returns:

true if debugging output is on

debugTipText

public String debugTipText()

Returns the tip text for this property

Returns:

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

getAlgorithmStart

public String getAlgorithmStart()

Returns the time/date string the algorithm was started

Returns:

the time and date the algorithm was started

getCycleStart

public String getCycleStart()

Returns the time/date string the cycle was started

Returns:

the time and date the cycle was started

getCycleEnd

public String getCycleEnd()

Returns the time/date string the cycle ended

Returns:

the time and date the cycle ended

toString

public String toString()

Returns a String containing the result information of the algorithm.

Overrides:

toString in class Object

Returns:

the String containing the result information

getRevision

public String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class AbstractAssociator

Returns:

the revision

main

public static void main(String[] args)

Main method.

Parameters:

args - commandline options, use -h for help