FPGrowth (weka-dev 3.7.6-SNAPSHOT API)

java.lang.Object
- weka.associations.AbstractAssociator
- - weka.associations.FPGrowth

All Implemented Interfaces:: Serializable, Cloneable, AssociationRulesProducer, Associator, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler

public class FPGrowth
extends AbstractAssociator
implements AssociationRulesProducer, OptionHandler, TechnicalInformationHandler

Class implementing the FP-growth algorithm for finding large item sets without candidate generation. Iteratively reduces the minimum support until it finds the required number of rules with the given minimum metric. For more information see:

J. Han, J.Pei, Y. Yin: Mining frequent patterns without candidate generation. In: Proceedings of the 2000 ACM-SIGMID International Conference on Management of Data, 1-12, 2000.

BibTeX:

 @inproceedings{Han2000,
    author = {J. Han and J.Pei and Y. Yin},
    booktitle = {Proceedings of the 2000 ACM-SIGMID International Conference on Management of Data},
    pages = {1-12},
    title = {Mining frequent patterns without candidate generation},
    year = {2000}
 }

Valid options are:

 -P <attribute index of positive value>
  Set the index of the attribute value to consider as 'positive'
  for binary attributes in normal dense instances. Index 2 is always
  used for sparse instances. (default = 2)

 -I <max items>
  The maximum number of items to include in large items sets (and rules). (default = -1, i.e. no limit.)

 -N <require number of rules>
  The required number of rules. (default = 10)

 -T <0=confidence | 1=lift | 2=leverage | 3=Conviction>
  The metric by which to rank rules. (default = confidence)

 -C <minimum metric score of a rule>
  The minimum metric score of a rule. (default = 0.9)

 -U <upper bound for minimum support>
  Upper bound for minimum support. (default = 1.0)

 -M <lower bound for minimum support>
  The lower bound for the minimum support. (default = 0.1)

 -D <delta for minimum support>
  The delta by which the minimum support is decreased in
  each iteration. (default = 0.05)

 -S
  Find all rules that meet the lower bound on
  minimum support and the minimum metric constraint.
  Turning this mode on will disable the iterative support reduction
  procedure to find the specified number of rules.

 -transactions <comma separated list of attribute names>
  Only consider transactions that contain these items (default = no restriction)

 -rules <comma separated list of attribute names>
  Only print rules that contain these items. (default = no restriction)

 -use-or
  Use OR instead of AND for must contain list(s). Use in conjunction
  with -transactions and/or -rules

Version:: $Revision: 8034 $
Author:: Mark Hall (mhall{[at]}pentaho{[dot]}com)
See Also:: Serialized Form

Constructor Summary

Constructors
Constructor and Description

FPGrowth()
Construct a new FPGrowth object.

Constructors
Constructor and Description
`FPGrowth()` Construct a new FPGrowth object.

Method Summary

Methods
Modifier and Type	Method and Description
`void`	`buildAssociations(Instances data)` Method that generates all large item sets with a minimum support, and from these all association rules with a minimum metric (i.e.
`boolean`	`canProduceRules()` Returns true if this AssociationRulesProducer can actually produce rules.
`String`	`deltaTipText()` Returns the tip text for this property
`String`	`findAllRulesForSupportLevelTipText()` Tip text for this property suitable for displaying in the GUI.
`static List<AssociationRule>`	`generateRulesBruteForce(weka.associations.FPGrowth.FrequentItemSets largeItemSets, DefaultAssociationRule.METRIC_TYPE metricToUse, double metricThreshold, int upperBoundMinSuppAsInstances, int lowerBoundMinSuppAsInstances, int totalTransactions)` Generate all association rules, from the supplied frequet item sets, that meet a given minimum metric threshold.
`AssociationRules`	`getAssociationRules()` Gets the list of mined association rules.
`Capabilities`	`getCapabilities()` Returns default capabilities of the classifier.
`double`	`getDelta()` Get the value of delta.
`boolean`	`getFindAllRulesForSupportLevel()` Get whether all rules meeting the lower bound on min support and the minimum metric threshold are to be found.
`double`	`getLowerBoundMinSupport()` Get the value of lowerBoundMinSupport.
`int`	`getMaxNumberOfItems()` Gets the maximum number of items to be included in large item sets.
`SelectedTag`	`getMetricType()` Get the metric type to use.
`double`	`getMinMetric()` Get the value of minConfidence.
`int`	`getNumRulesToFind()` Get the number of rules to find.
`String[]`	`getOptions()` Gets the current settings of the classifier.
`int`	`getPositiveIndex()` Get the index of the attribute value to consider as positive for binary attributes in normal dense instances.
`String`	`getRevision()` Returns the revision string.
`String[]`	`getRuleMetricNames()` Gets a list of the names of the metrics output for each rule.
`String`	`getRulesMustContain()` Get the comma separated list of items that rules must contain in order to be output.
`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.
`String`	`getTransactionsMustContain()` Gets the comma separated list of items that transactions must contain in order to be considered for large item sets and rules.
`double`	`getUpperBoundMinSupport()` Get the value of upperBoundMinSupport.
`boolean`	`getUseORForMustContainList()` Gets whether OR is to be used rather than AND when considering must contain lists.
`String`	`globalInfo()` Returns a string describing this associator
`String`	`graph(weka.associations.FPGrowth.FPTreeRoot tree)` Assemble a dot graph representation of the FP-tree.
`Enumeration<Option>`	`listOptions()` Returns an enumeration describing the available options.
`String`	`lowerBoundMinSupportTipText()` Returns the tip text for this property
`static void`	`main(String[] args)` Main method.
`String`	`maxNumberOfItemsTipText()` Tip text for this property suitable for displaying in the GUI.
`String`	`metricTypeTipText()` Tip text for this property suitable for displaying in the GUI.
`String`	`minMetricTipText()` Returns the tip text for this property
`String`	`numRulesToFindTipText()` Tip text for this property suitable for displaying in the GUI.
`String`	`positiveIndexTipText()` Tip text for this property suitable for displaying in the GUI.
`static List<AssociationRule>`	`pruneRules(List<AssociationRule> rulesToPrune, ArrayList<Item> itemsToConsider, boolean useOr)`
`void`	`resetOptions()` Reset all options to their default values.
`String`	`rulesMustContainTipText()` Returns the tip text for this property
`void`	`setDelta(double v)` Set the value of delta.
`void`	`setFindAllRulesForSupportLevel(boolean s)` If true then turn off the iterative support reduction method of finding x rules that meet the minimum support and metric thresholds and just return all the rules that meet the lower bound on minimum support and the minimum metric.
`void`	`setLowerBoundMinSupport(double v)` Set the value of lowerBoundMinSupport.
`void`	`setMaxNumberOfItems(int max)` Set the maximum number of items to include in large items sets.
`void`	`setMetricType(SelectedTag d)` Set the metric type to use.
`void`	`setMinMetric(double v)` Set the value of minConfidence.
`void`	`setNumRulesToFind(int numR)` Set the desired number of rules to find.
`void`	`setOffDiskReportingFrequency(int freq)` Set how often to report some progress when the data is being read incrementally off of the disk rather than loaded into memory.
`void`	`setOptions(String[] options)` Parses a given list of options.
`void`	`setPositiveIndex(int index)` Set the index of the attribute value to consider as positive for binary attributes in normal dense instances.
`void`	`setRulesMustContain(String list)` Set the comma separated list of items that rules must contain in order to be output.
`void`	`setTransactionsMustContain(String list)` Set the comma separated list of items that transactions must contain in order to be considered for large item sets and rules.
`void`	`setUpperBoundMinSupport(double v)` Set the value of upperBoundMinSupport.
`void`	`setUseORForMustContainList(boolean b)` Set whether to use OR rather than AND when considering must contain lists.
`String`	`toString()` Output the association rules.
`String`	`transactionsMustContainTipText()` Returns the tip text for this property
`String`	`upperBoundMinSupportTipText()` Returns the tip text for this property
`String`	`useORForMustContainListTipText()` Returns the tip text for this property

Methods inherited from class weka.associations.AbstractAssociator
forName, makeCopies, makeCopy, runAssociator

Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

- Constructor Detail
  - FPGrowth
```
public FPGrowth()
```
    Construct a new FPGrowth object.
- Method Detail
  - generateRulesBruteForce
```
public static List<AssociationRule> generateRulesBruteForce(weka.associations.FPGrowth.FrequentItemSets largeItemSets,
                                            DefaultAssociationRule.METRIC_TYPE metricToUse,
                                            double metricThreshold,
                                            int upperBoundMinSuppAsInstances,
                                            int lowerBoundMinSuppAsInstances,
                                            int totalTransactions)
```
    Generate all association rules, from the supplied frequet item sets, that meet a given minimum metric threshold. Uses a brute force approach.
    
    Parameters:
    largeItemSets - the set of frequent item sets
    metricToUse - the metric to use
    metricThreshold - the threshold value that a rule must meet
    upperBoundMinSuppAsInstances - the upper bound on the support in order to accept the rule
    lowerBoundMinSuppAsInstances - the lower bound on the support in order to accept the rule
    totalTransactions - the total number of transactions in the data
    
    Returns:
    a list of association rules
  - pruneRules
```
public static List<AssociationRule> pruneRules(List<AssociationRule> rulesToPrune,
                               ArrayList<Item> itemsToConsider,
                               boolean useOr)
```
  - getCapabilities
```
public Capabilities getCapabilities()
```
    Returns default capabilities of the classifier.
    
    Specified by:
    
    getCapabilities in interface Associator
    
    Specified by:
    
    getCapabilities in interface CapabilitiesHandler
    
    Overrides:
    
    getCapabilities in class AbstractAssociator
    
    Returns:
    the capabilities of this classifier
    See Also:
    Capabilities
  - globalInfo
```
public String globalInfo()
```
    Returns a string describing this associator
    
    Returns:
    a description of the evaluator suitable for displaying in the explorer/experimenter gui
  - getTechnicalInformation
```
public 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 TechnicalInformationHandler
    
    Returns:
    the technical information about this class
  - resetOptions
```
public void resetOptions()
```
    Reset all options to their default values.
  - positiveIndexTipText
```
public String positiveIndexTipText()
```
    Tip text for this property suitable for displaying in the GUI.
    
    Returns:
    the tip text for this property.
  - setPositiveIndex
```
public void setPositiveIndex(int index)
```
    Set the index of the attribute value to consider as positive for binary attributes in normal dense instances. Index 1 is always used for sparse instances.
    
    Parameters:
    index - the index to use for positive values in binary attributes.
  - getPositiveIndex
```
public int getPositiveIndex()
```
    Get the index of the attribute value to consider as positive for binary attributes in normal dense instances. Index 1 is always used for sparse instances.
    
    Returns:
    the index to use for positive values in binary attributes.
  - setNumRulesToFind
```
public void setNumRulesToFind(int numR)
```
    Set the desired number of rules to find.
    
    Parameters:
    numR - the number of rules to find.
  - getNumRulesToFind
```
public int getNumRulesToFind()
```
    Get the number of rules to find.
    
    Returns:
    the number of rules to find.
  - numRulesToFindTipText
```
public String numRulesToFindTipText()
```
    Tip text for this property suitable for displaying in the GUI.
    
    Returns:
    the tip text for this property.
  - setMetricType
```
public void setMetricType(SelectedTag d)
```
    Set the metric type to use.
    
    Parameters:
    d - the metric type
  - setMaxNumberOfItems
```
public void setMaxNumberOfItems(int max)
```
    Set the maximum number of items to include in large items sets.
    
    Parameters:
    max - the maxim number of items to include in large item sets.
  - getMaxNumberOfItems
```
public int getMaxNumberOfItems()
```
    Gets the maximum number of items to be included in large item sets.
    
    Returns:
    the maximum number of items to be included in large items sets.
  - maxNumberOfItemsTipText
```
public String maxNumberOfItemsTipText()
```
    Tip text for this property suitable for displaying in the GUI.
    
    Returns:
    the tip text for this property.
  - getMetricType
```
public SelectedTag getMetricType()
```
    Get the metric type to use.
    
    Returns:
    the metric type to use.
  - metricTypeTipText
```
public String metricTypeTipText()
```
    Tip text for this property suitable for displaying in the GUI.
    
    Returns:
    the tip text for this property.
  - minMetricTipText
```
public String minMetricTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getMinMetric
```
public double getMinMetric()
```
    Get the value of minConfidence.
    
    Returns:
    Value of minConfidence.
  - setMinMetric
```
public void setMinMetric(double v)
```
    Set the value of minConfidence.
    
    Parameters:
    v - Value to assign to minConfidence.
  - transactionsMustContainTipText
```
public String transactionsMustContainTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setTransactionsMustContain
```
public void setTransactionsMustContain(String list)
```
    Set the comma separated list of items that transactions must contain in order to be considered for large item sets and rules.
    
    Parameters:
    list - a comma separated list of items (empty string indicates no restriction on the transactions).
  - getTransactionsMustContain
```
public String getTransactionsMustContain()
```
    Gets the comma separated list of items that transactions must contain in order to be considered for large item sets and rules.
    
    Returns:
    return the comma separated list of items that transactions must contain.
  - rulesMustContainTipText
```
public String rulesMustContainTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setRulesMustContain
```
public void setRulesMustContain(String list)
```
    Set the comma separated list of items that rules must contain in order to be output.
    
    Parameters:
    list - a comma separated list of items (empty string indicates no restriction on the rules).
  - getRulesMustContain
```
public String getRulesMustContain()
```
    Get the comma separated list of items that rules must contain in order to be output.
    
    Returns:
    the comma separated list of items that rules must contain in order to be output.
  - useORForMustContainListTipText
```
public String useORForMustContainListTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setUseORForMustContainList
```
public void setUseORForMustContainList(boolean b)
```
    Set whether to use OR rather than AND when considering must contain lists.
    
    Parameters:
    b - true if OR should be used instead of AND when considering transaction and rules must contain lists.
  - getUseORForMustContainList
```
public boolean getUseORForMustContainList()
```
    Gets whether OR is to be used rather than AND when considering must contain lists.
    
    Returns:
    true if OR is used instead of AND.
  - deltaTipText
```
public String deltaTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying, in the explorer/experimenter gui
  - getDelta
```
public double getDelta()
```
    Get the value of delta.
    
    Returns:
    Value of delta.
  - setDelta
```
public void setDelta(double v)
```
    Set the value of delta.
    
    Parameters:
    v - Value to assign to delta.
  - lowerBoundMinSupportTipText
```
public String lowerBoundMinSupportTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getLowerBoundMinSupport
```
public double getLowerBoundMinSupport()
```
    Get the value of lowerBoundMinSupport.
    
    Returns:
    Value of lowerBoundMinSupport.
  - setLowerBoundMinSupport
```
public void setLowerBoundMinSupport(double v)
```
    Set the value of lowerBoundMinSupport.
    
    Parameters:
    v - Value to assign to lowerBoundMinSupport.
  - upperBoundMinSupportTipText
```
public String upperBoundMinSupportTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getUpperBoundMinSupport
```
public double getUpperBoundMinSupport()
```
    Get the value of upperBoundMinSupport.
    
    Returns:
    Value of upperBoundMinSupport.
  - setUpperBoundMinSupport
```
public void setUpperBoundMinSupport(double v)
```
    Set the value of upperBoundMinSupport.
    
    Parameters:
    v - Value to assign to upperBoundMinSupport.
  - findAllRulesForSupportLevelTipText
```
public String findAllRulesForSupportLevelTipText()
```
    Tip text for this property suitable for displaying in the GUI.
    
    Returns:
    the tip text for this property.
  - setFindAllRulesForSupportLevel
```
public void setFindAllRulesForSupportLevel(boolean s)
```
    If true then turn off the iterative support reduction method of finding x rules that meet the minimum support and metric thresholds and just return all the rules that meet the lower bound on minimum support and the minimum metric.
    
    Parameters:
    s - true if all rules meeting the lower bound on the support and minimum metric thresholds are to be found.
  - getFindAllRulesForSupportLevel
```
public boolean getFindAllRulesForSupportLevel()
```
    Get whether all rules meeting the lower bound on min support and the minimum metric threshold are to be found.
    
    Returns:
    true if all rules meeting the lower bound on min support and the min metric threshold are to be found.
  - setOffDiskReportingFrequency
```
public void setOffDiskReportingFrequency(int freq)
```
    Set how often to report some progress when the data is being read incrementally off of the disk rather than loaded into memory.
    
    Parameters:
    freq - the frequency to print progress.
  - getAssociationRules
```
public AssociationRules getAssociationRules()
```
    Gets the list of mined association rules.
    
    Specified by:
    
    getAssociationRules in interface AssociationRulesProducer
    
    Returns:
    the list of association rules discovered during mining. Returns null if mining hasn't been performed yet.
  - getRuleMetricNames
```
public String[] getRuleMetricNames()
```
    Gets a list of the names of the metrics output for each rule. This list should be the same (in terms of the names and order thereof) as that produced by AssociationRule.getMetricNamesForRule().
    
    Specified by:
    
    getRuleMetricNames in interface AssociationRulesProducer
    
    Returns:
    an array of the names of the metrics available for each rule learned by this producer.
  - canProduceRules
```
public boolean canProduceRules()
```
    Returns true if this AssociationRulesProducer can actually produce rules. Most implementing classes will always return true from this method (obviously :-)). However, an implementing class that actually acts as a wrapper around things that may or may not implement AssociationRulesProducer will want to return false if the thing they wrap can't produce rules.
    
    Specified by:
    
    canProduceRules in interface AssociationRulesProducer
    
    Returns:
    true if this producer can produce rules in its current configuration
  - listOptions
```
public Enumeration<Option> listOptions()
```
    Returns an enumeration describing the available options.
    
    Specified by:
    
    listOptions in interface OptionHandler
    
    Returns:
    an enumeration of all the available options.
  - setOptions
```
public void setOptions(String[] options)
                throws Exception
```
    Parses a given list of options.
    Valid options are:
```
 -P <attribute index of positive value>
  Set the index of the attribute value to consider as 'positive'
  for binary attributes in normal dense instances. Index 2 is always
  used for sparse instances. (default = 2)
```
```
 -I <max items>
  The maximum number of items to include in large items sets (and rules). (default = -1, i.e. no limit.)
```
```
 -N <require number of rules>
  The required number of rules. (default = 10)
```
```
 -T <0=confidence | 1=lift | 2=leverage | 3=Conviction>
  The metric by which to rank rules. (default = confidence)
```
```
 -C <minimum metric score of a rule>
  The minimum metric score of a rule. (default = 0.9)
```
```
 -U <upper bound for minimum support>
  Upper bound for minimum support. (default = 1.0)
```
```
 -M <lower bound for minimum support>
  The lower bound for the minimum support. (default = 0.1)
```
```
 -D <delta for minimum support>
  The delta by which the minimum support is decreased in
  each iteration. (default = 0.05)
```
```
 -S
  Find all rules that meet the lower bound on
  minimum support and the minimum metric constraint.
  Turning this mode on will disable the iterative support reduction
  procedure to find the specified number of rules.
```
```
 -transactions <comma separated list of attribute names>
  Only consider transactions that contain these items (default = no restriction)
```
```
 -rules <comma separated list of attribute names>
  Only print rules that contain these items. (default = no restriction)
```
```
 -use-or
  Use OR instead of AND for must contain list(s). Use in conjunction
  with -transactions and/or -rules
```
    Specified by:
    
    setOptions in interface OptionHandler
    
    Parameters:
    options - the list of options as an array of strings
    
    Throws:
    
    Exception - if an option is not supported
  - getOptions
```
public String[] getOptions()
```
    Gets the current settings of the classifier.
    
    Specified by:
    
    getOptions in interface OptionHandler
    
    Returns:
    an array of strings suitable for passing to setOptions
  - buildAssociations
```
public void buildAssociations(Instances data)
                       throws Exception
```
    Method that generates all large item sets with a minimum support, and from these all association rules with a minimum metric (i.e. confidence, lift etc.).
    
    Specified by:
    
    buildAssociations in interface Associator
    
    Parameters:
    data - the instances to be used for generating the associations
    
    Throws:
    
    Exception - if rules can't be built successfully
  - toString
```
public String toString()
```
    Output the association rules.
    
    Overrides:
    
    toString in class Object
    
    Returns:
    a string representation of the model.
  - graph
```
public String graph(weka.associations.FPGrowth.FPTreeRoot tree)
```
    Assemble a dot graph representation of the FP-tree.
    
    Parameters:
    tree - the root of the FP-tree
    
    Returns:
    a graph representation as a String in dot format.
  - 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 - the commandline options

Class FPGrowth

Constructor Summary

Method Summary

Methods inherited from class weka.associations.AbstractAssociator

Methods inherited from class java.lang.Object

Constructor Detail

FPGrowth

Method Detail

generateRulesBruteForce

pruneRules

getCapabilities

globalInfo

getTechnicalInformation

resetOptions

positiveIndexTipText

setPositiveIndex

getPositiveIndex

setNumRulesToFind

getNumRulesToFind

numRulesToFindTipText

setMetricType

setMaxNumberOfItems

getMaxNumberOfItems

maxNumberOfItemsTipText

getMetricType

metricTypeTipText

minMetricTipText

getMinMetric

setMinMetric

transactionsMustContainTipText

setTransactionsMustContain

getTransactionsMustContain

rulesMustContainTipText

setRulesMustContain

getRulesMustContain

useORForMustContainListTipText

setUseORForMustContainList

getUseORForMustContainList

deltaTipText

getDelta

setDelta

lowerBoundMinSupportTipText

getLowerBoundMinSupport

setLowerBoundMinSupport

upperBoundMinSupportTipText

getUpperBoundMinSupport

setUpperBoundMinSupport

findAllRulesForSupportLevelTipText

setFindAllRulesForSupportLevel

getFindAllRulesForSupportLevel

setOffDiskReportingFrequency

getAssociationRules

getRuleMetricNames

canProduceRules

listOptions

setOptions

getOptions

buildAssociations

toString

graph

getRevision

main