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Class weka.associations.Apriori

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

public class Apriori
extends Associator
implements OptionHandler
Class implementing an Apriori-type algorithm. Iteratively reduces the minimum support until it finds the required number of rules with the given minimum confidence.

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).

-T type of metric by which to sort rules
0 = confidence | 1 = lift | 2 = leverage | 3 = Conviction.

-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).

-U upper bound for minimum support
The upper bound for minimum support. Don't explicitly look for rules with more than this level of support.

-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).

-R
If set then columns that contain all missing values are removed from the data. -I
If set the itemsets found are also output (default = no).

Version:
$Revision: 1.11 $
Author:
Eibe Frank (eibe@cs.waikato.ac.nz)
Author:
Mark Hall (mhall@cs.waikato.ac.nz)

Variable Index

 o TAGS_SELECTION
 

Constructor Index

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

Method Index

 o buildAssociations(Instances)
Method that generates all large itemsets with a minimum support, and from these all association rules with a minimum confidence.
 o deltaTipText()
Returns the tip text for this property
 o getDelta()
Get the value of delta.
 o getLowerBoundMinSupport()
Get the value of lowerBoundMinSupport.
 o getMetricType()
Get the metric type
 o getMinMetric()
Get the value of minConfidence.
 o getNumRules()
Get the value of numRules.
 o getOptions()
Gets the current settings of the Apriori object.
 o getRemoveAllMissingCols()
Returns whether columns containing all missing values are to be removed
 o getSignificanceLevel()
Get the value of significanceLevel.
 o getUpperBoundMinSupport()
Get the value of upperBoundMinSupport.
 o globalInfo()
Returns a string describing this associator
 o listOptions()
Returns an enumeration describing the available options
 o lowerBoundMinSupportTipText()
Returns the tip text for this property
 o main(String[])
Main method for testing this class.
 o metricTypeTipText()
Returns the tip text for this property
 o minMetricTipText()
Returns the tip text for this property
 o numRulesTipText()
Returns the tip text for this property
 o removeAllMissingColsTipText()
Returns the tip text for this property
 o resetOptions()
Resets the options to the default values.
 o setDelta(double)
Set the value of delta.
 o setLowerBoundMinSupport(double)
Set the value of lowerBoundMinSupport.
 o setMetricType(SelectedTag)
Set the metric type for ranking rules
 o setMinMetric(double)
Set the value of minConfidence.
 o setNumRules(int)
Set the value of numRules.
 o setOptions(String[])
Parses a given list of options.
 o setRemoveAllMissingCols(boolean)
Remove columns containing all missing values.
 o setSignificanceLevel(double)
Set the value of significanceLevel.
 o setUpperBoundMinSupport(double)
Set the value of upperBoundMinSupport.
 o significanceLevelTipText()
Returns the tip text for this property
 o toString()
Outputs the size of all the generated sets of itemsets and the rules.
 o upperBoundMinSupportTipText()
Returns the tip text for this property

Field Detail

 o TAGS_SELECTION
public static final Tag[] TAGS_SELECTION

Constructor Detail

 o Apriori
public Apriori()
          Constructor that allows to sets default values for the minimum confidence and the maximum number of rules the minimum confidence.

Method Detail

 o globalInfo
public java.lang.String globalInfo()
          Returns a string describing this associator
Returns:
a description of the evaluator suitable for displaying in the explorer/experimenter gui
 o resetOptions
public void resetOptions()
          Resets the options to the default values.
 o buildAssociations
public void buildAssociations(Instances instances) throws java.lang.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:
java.lang.Exception - if rules can't be built successfully
Overrides:
buildAssociations in class Associator
 o listOptions
public java.util.Enumeration listOptions()
          Returns an enumeration describing the available options
Returns:
an enumeration of all the available options
 o setOptions
public void setOptions(java.lang.String options[]) throws java.lang.Exception
          Parses a given list of options. Valid options are:

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

-T type of metric by which to sort rules
0 = confidence | 1 = lift | 2 = leverage | 3 = Conviction.

-C minimum metric score 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). -U upper bound for minimum support
The upper bound for minimum support. Don't explicitly look for rules with more than this level of support.

-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).

-V
If set then progress is reported iteratively during execution.

-R
If set then columns that contain all missing values are removed from the data.

Parameters:
options - the list of options as an array of strings
Throws:
java.lang.Exception - if an option is not supported
 o getOptions
public java.lang.String[] getOptions()
          Gets the current settings of the Apriori object.
Returns:
an array of strings suitable for passing to setOptions
 o toString
public java.lang.String toString()
          Outputs the size of all the generated sets of itemsets and the rules.
Overrides:
toString in class java.lang.Object
 o removeAllMissingColsTipText
public java.lang.String removeAllMissingColsTipText()
          Returns the tip text for this property
Returns:
tip text for this property suitable for displaying in the explorer/experimenter gui
 o setRemoveAllMissingCols
public void setRemoveAllMissingCols(boolean r)
          Remove columns containing all missing values.
Parameters:
r - true if cols are to be removed.
 o getRemoveAllMissingCols
public boolean getRemoveAllMissingCols()
          Returns whether columns containing all missing values are to be removed
Returns:
true if columns are to be removed.
 o upperBoundMinSupportTipText
public java.lang.String upperBoundMinSupportTipText()
          Returns the tip text for this property
Returns:
tip text for this property suitable for displaying in the explorer/experimenter gui
 o getUpperBoundMinSupport
public double getUpperBoundMinSupport()
          Get the value of upperBoundMinSupport.
Returns:
Value of upperBoundMinSupport.
 o setUpperBoundMinSupport
public void setUpperBoundMinSupport(double v)
          Set the value of upperBoundMinSupport.
Parameters:
v - Value to assign to upperBoundMinSupport.
 o lowerBoundMinSupportTipText
public java.lang.String lowerBoundMinSupportTipText()
          Returns the tip text for this property
Returns:
tip text for this property suitable for displaying in the explorer/experimenter gui
 o getLowerBoundMinSupport
public double getLowerBoundMinSupport()
          Get the value of lowerBoundMinSupport.
Returns:
Value of lowerBoundMinSupport.
 o setLowerBoundMinSupport
public void setLowerBoundMinSupport(double v)
          Set the value of lowerBoundMinSupport.
Parameters:
v - Value to assign to lowerBoundMinSupport.
 o getMetricType
public SelectedTag getMetricType()
          Get the metric type
Returns:
the type of metric to use for ranking rules
 o metricTypeTipText
public java.lang.String metricTypeTipText()
          Returns the tip text for this property
Returns:
tip text for this property suitable for displaying in the explorer/experimenter gui
 o setMetricType
public void setMetricType(SelectedTag d)
          Set the metric type for ranking rules
Parameters:
d - the type of metric
 o minMetricTipText
public java.lang.String minMetricTipText()
          Returns the tip text for this property
Returns:
tip text for this property suitable for displaying in the explorer/experimenter gui
 o getMinMetric
public double getMinMetric()
          Get the value of minConfidence.
Returns:
Value of minConfidence.
 o setMinMetric
public void setMinMetric(double v)
          Set the value of minConfidence.
Parameters:
v - Value to assign to minConfidence.
 o numRulesTipText
public java.lang.String numRulesTipText()
          Returns the tip text for this property
Returns:
tip text for this property suitable for displaying in the explorer/experimenter gui
 o getNumRules
public int getNumRules()
          Get the value of numRules.
Returns:
Value of numRules.
 o setNumRules
public void setNumRules(int v)
          Set the value of numRules.
Parameters:
v - Value to assign to numRules.
 o deltaTipText
public java.lang.String deltaTipText()
          Returns the tip text for this property
Returns:
tip text for this property suitable for displaying in the explorer/experimenter gui
 o getDelta
public double getDelta()
          Get the value of delta.
Returns:
Value of delta.
 o setDelta
public void setDelta(double v)
          Set the value of delta.
Parameters:
v - Value to assign to delta.
 o significanceLevelTipText
public java.lang.String significanceLevelTipText()
          Returns the tip text for this property
Returns:
tip text for this property suitable for displaying in the explorer/experimenter gui
 o getSignificanceLevel
public double getSignificanceLevel()
          Get the value of significanceLevel.
Returns:
Value of significanceLevel.
 o setSignificanceLevel
public void setSignificanceLevel(double v)
          Set the value of significanceLevel.
Parameters:
v - Value to assign to significanceLevel.
 o main
public static void main(java.lang.String options[])
          Main method for testing this class.

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