Mining Negative Rules Using GRD

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.

• Type: Conference
• Year: 2004
• Where: PAKDD
• Authors: Dhananjay R. Thiruvady, Geoffrey I. Webb
• Keywords: Association Rule Discovery, Data Mining, Interesting Rule Discovery, PAKDD 2004, Rule Discovery