Geometric algorithms for a minimum cost assignment problem
Takeshi Tokuyama, Jun Nakano
SCG 1991
We discuss data mining based on association rules for two numeric attributes and one Boolean attribute. For example, in a database of bank customers, "Age" and "Balance" are two numeric attributes, and "CardLoan" is a Boolean attribute. Taking the pair (Age, Balance) as a point in two-dimensional space, we consider an association rule of the form ((Age, Balance) ∈ P) ⇒ (CardLoan = Yes), which implies that bank customers whose ages and balances fall in a planar region P tend to use card loan with a high probability. We consider two classes of regions, rectangles and admissible (i.e. connected and x-monotone) regions. For each class, we propose efficient algorithms for computing the regions that give optimal association rules for gain, support, and confidence, respectively. We have implemented the algorithms for admissible regions, and constructed a system for visualizing the rules.
Takeshi Tokuyama, Jun Nakano
SCG 1991
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IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Takeshi Fukuda, Yasuhiko Morimoto, et al.
ACM TODS
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