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Mining negative rules using GRD
conference contributionposted on 2004-01-01, 00:00 authored by Dhananjay ThiruvadyDhananjay Thiruvady, G I Webb
© Springer-Verlag Berlin Heidelberg 2004. GRD is an algorithm for k-most interesting rule discovery. In contrast to association rule discovery, GRD does not require the use of a minimum support constraint. Rather, the user must specify a measure of interestingness and the number of rules sought (k). This paper reports efficient techniques to extend GRD to support mining of negative rules. We demonstrate that the new approach provides tractable discovery of both negative and positive rules.