An Extension of Totohasina’s Normalization Theory of Quality Measures of Association Rules

Armand, André Totohasina and Daniel Rajaonasy Feno

International Journal of Mathematics and Mathematical Sciences, 2019, vol. 2019, 1-7

Abstract:

In the context of binary data mining, for unifying view on probabilistic quality measures of association rules, Totohasina’s theory of normalization of quality measures of association rules primarily based on affine homeomorphism presents some drawbacks. Indeed, it cannot normalize some interestingness measures which are explained below. This paper presents an extension of it, as a new normalization method based on proper homographic homeomorphism that appears most consequent.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jijmms:7829805

DOI: 10.1155/2019/7829805

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