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Title:

Quantitative Associaton Rules Based on Half-Spaces: An Optimization Approach

Document type:
Technical Report
Author(s):
Ulrich Rueckert; Lothar Richter; Stefan Kramer
Abstract:
We tackle the problem of finding association rules for quantitative data. Whereas most of the previous approaches operate on hyperrectangles, we propose a representation based on half-spaces. Consequently, the left-hand side and right-hand side of an association rule does not contain a conjunction of items or intervals, but a weighted sum of variables tested against a threshold. Since the downward closure property does not hold for such rules, we propose an optimization setting for finding local...     »
Keywords:
Association Rules; Optimization; Data Mining
Year:
2004
Year / month:
2004-08-01 00:00:00
Pages:
17
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