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

Autor: Armand, André Totohasina, Daniel Rajaonasy Feno
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: International Journal of Mathematics and Mathematical Sciences, Vol 2019 (2019)
Druh dokumentu: article
ISSN: 0161-1712
1687-0425
DOI: 10.1155/2019/7829805
Popis: 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.
Databáze: Directory of Open Access Journals
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