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

Armand | Zendy; André Totohasina | Zendy; Daniel Rajaonasy Feno | Zendy

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

Author(s) -

Armand,

André Totohasina,

Daniel Rajaonasy Feno

Publication year - 2019

Publication title -

international journal of mathematics and mathematical sciences

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.21

H-Index - 39

eISSN - 1687-0425

pISSN - 0161-1712

DOI - 10.1155/2019/7829805

Subject(s) - normalization (sociology) , mathematics , probabilistic logic , extension (predicate logic) , affine transformation , binary number , data mining , computer science , pure mathematics , statistics , arithmetic , sociology , anthropology , programming language

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.

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