document: Discovering associations with numeric variables This paper further develops Aumann and Lindell 's ( 3 ) proposal for a variant of association rules for which the consequent is a numeric variable . It is argued that these rules can discover useful interactions with numeric data that can not be discovered directly using traditional association rules with discretization . Alternative measures for identifying interesting rules are proposed . Efficient algorithms are presented that enable these rules to be discovered for dense data sets for which application of Auman and Lindell 's algorithm is infeasible .
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