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PAKDD
2004
ACM

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Mining Negative Rules Using GRD

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Mining Negative Rules Using GRD

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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.

Dhananjay R. Thiruvady, Geoffrey I. Webb

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Association Rule Discovery | Data Mining | Interesting Rule Discovery | PAKDD 2004 | Rule Discovery |

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Added	02 Jul 2010
Updated	02 Jul 2010
Type	Conference
Year	2004
Where	PAKDD
Authors	Dhananjay R. Thiruvady, Geoffrey I. Webb

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