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Class weka.associations.Apriori

java.lang.Object
   |
   +----weka.associations.Associator
           |
           +----weka.associations.Apriori

public class Apriori

extends Associator

implements OptionHandler

Reference: R. Agrawal, R. Srikant (1994). Fast algorithms for mining association rules in large databases . Proc International Conference on Very Large Databases, pp. 478-499. Santiage, Chile: Morgan Kaufmann, Los Altos, CA.

Valid options are:

-N required number of rules
The required number of rules (default: 10).

-C minimum confidence of a rule
The minimum confidence of a rule (default: 0.9).

-D delta for minimum support
The delta by which the minimum support is decreased in each iteration (default: 0.05). -M lower bound for minimum support
The lower bound for the minimum support (default = 0.1).

-S significance level
If used, rules are tested for significance at the given level. Slower (default = no significance testing).

-I
If set the itemsets found are also output (default = no).

Version:

$Revision: 1.4 $

Author:

Eibe Frank (eibe@cs.waikato.ac.nz)

Apriori()

Constructor that allows to sets default values for the minimum confidence and the maximum number of rules the minimum confidence.

buildAssociations(Instances)

Method that generates all large itemsets with a minimum support, and from these all association rules with a minimum confidence.

getDelta()

Get the value of delta.

getLowerBoundMinSupport()

Get the value of lowerBoundMinSupport.

getMinConfidence()

Get the value of minConfidence.

getMinSupport()

Get the value of minSupport.

getNumRules()

Get the value of numRules.

getOptions()

Gets the current settings of the Apriori object.

getSignificanceLevel()

Get the value of significanceLevel.

listOptions()

Returns an enumeration describing the available options

main(String[])

Main method for testing this class.

resetOptions()

Resets the options to the default values.

setDelta(double)

Set the value of delta.

setLowerBoundMinSupport(double)

Set the value of lowerBoundMinSupport.

setMinConfidence(double)

Set the value of minConfidence.

setMinSupport(double)

Set the value of minSupport.

setNumRules(int)

Set the value of numRules.

setOptions(String[])

Parses a given list of options.

setSignificanceLevel(double)

Set the value of significanceLevel.

toString()

Outputs the size of all the generated sets of itemsets and the rules.

 public Apriori()

Constructor that allows to sets default values for the minimum confidence and the maximum number of rules the minimum confidence.

 public void resetOptions()

Resets the options to the default values.

 public void buildAssociations(Instances instances) throws Exception

Method that generates all large itemsets with a minimum support, and from these all association rules with a minimum confidence.

Parameters:

instances - the instances to be used for generating the associations

Throws: Exception

if rules can't be built successfully

Overrides:

buildAssociations in class Associator

 public Enumeration listOptions()

Returns an enumeration describing the available options

Returns:

an enumeration of all the available options

 public void setOptions(String options[]) throws Exception

Parses a given list of options. Valid options are:

-N required number of rules
The required number of rules (default: 10).

-C minimum confidence of a rule
The minimum confidence of a rule (default: 0.9).

-D delta for minimum support
The delta by which the minimum support is decreased in each iteration (default: 0.05). -M lower bound for minimum support
The lower bound for the minimum support (default = 0.1).

-S significance level
If used, rules are tested for significance at the given level. Slower (default = no significance testing).

-I
If set the itemsets found are also output (default = no).

Parameters:

options - the list of options as an array of strings

Throws: Exception

if an option is not supported

 public String[] getOptions()

Gets the current settings of the Apriori object.

Returns:

an array of strings suitable for passing to setOptions

 public String toString()

Outputs the size of all the generated sets of itemsets and the rules.

Overrides:

toString in class Object

 public double getMinSupport()

Get the value of minSupport.

Returns:

Value of minSupport.

 public void setMinSupport(double v)

Set the value of minSupport.

Parameters:

v - Value to assign to minSupport.

 public double getLowerBoundMinSupport()

Get the value of lowerBoundMinSupport.

Returns:

Value of lowerBoundMinSupport.

 public void setLowerBoundMinSupport(double v)

Set the value of lowerBoundMinSupport.

Parameters:

v - Value to assign to lowerBoundMinSupport.

 public double getMinConfidence()

Get the value of minConfidence.

Returns:

Value of minConfidence.

 public void setMinConfidence(double v)

Set the value of minConfidence.

Parameters:

v - Value to assign to minConfidence.

 public int getNumRules()

Get the value of numRules.

Returns:

Value of numRules.

 public void setNumRules(int v)

Set the value of numRules.

Parameters:

v - Value to assign to numRules.

 public double getDelta()

Get the value of delta.

Returns:

Value of delta.

 public void setDelta(double v)

Set the value of delta.

Parameters:

v - Value to assign to delta.

 public double getSignificanceLevel()

Get the value of significanceLevel.

Returns:

Value of significanceLevel.

 public void setSignificanceLevel(double v)

Set the value of significanceLevel.

Parameters:

v - Value to assign to significanceLevel.

 public static void main(String options[])

Main method for testing this class.

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