Package javax.datamining.association

This package contains Java classes describing the settings and model for the association mining function.

See:
Description

Interface Summary

AssociationModel	An AssociationModel object contains the metadata, such as itemsets, rules, resulting from a model built using AssociationSettings.
AssociationRule	The interface AssociationRule defines a relationship between two itemsets where the antecendent implies the consequent.
AssociationRulesAlgorithmSettings	An AssociationRulesAlgorithmSettings is a place holder for association rules algorithm settings and serves as the common superclass for vendor specific algorithms.
AssociationRulesAlgorithmSettingsFactory	A factory class that creates instances of AssociationRulesAlgorithmSettings.
AssociationSettings	An AssociationSettings instance supports build settings specific to the association mining function.
AssociationSettingsFactory	A factory class that creates instances of AssociationSettings.
Itemset	An Itemset object is a component of an association rule and consists of items.
RulesFilter	The interface RulesFilter provides the specification for a rules filter to be used for retrieval of the rules that satisfies the specified conditions.
RulesFilterFactory	A factory class that creates instances of RulesFilter.

Class Summary

AssociationCapability	The enumeration AssociationCapability enumerates a list of the capabilities of the association rules function being supported in a particular implementation.
RuleComponentOption	The enumeration RuleComponentOption lists the components of the rule to be selected.
RuleProperty	The enumeration RuleProperty specifies the properties that may be available with an AssociationRule.

Package javax.datamining.association Description

This package contains Java classes describing the settings and model for the association mining function. Association analysis has been used in market basket analysis and the analysis of consumer behavior for the discovery of relationships of co-occurrences among a set of items, e.g., the presence of one pattern implies the presence of another pattern. Association identifies the attribute value combinations that occur frequently together in a given set of data. Association analysis is widely used in transaction data analysis for direct marketing, catalog design, and other business decision-making processes.