Discovering attributes dependency for categorical data set based on soft set theory for better decision making

Mohd Isa, Awang and Ahmad Nazari, Mohd Rose and Fadhilah, Ahmad (2015) Discovering attributes dependency for categorical data set based on soft set theory for better decision making. Applied Mathematical Sciences, 9 (130). pp. 6477-6490. ISSN 1312885X [P]

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Abstract

Attribute dependency concludes the association between attributes for better accurate decision making. However, the task involved in identifying the relation between categorical values in data set is a complex process. This main focus of this paper is to determine the attribute dependency in a real world application. The proposed method is based on the notion of mapping inclusion from the soft set theory. The categorical data is transformed to predicate and value set to discover the dependency among the attributes. The result shows that the attribute dependencies obtained are comparable to the rough set approach.

Item Type: Article
Uncontrolled Keywords: Categorical data set; Attribute dependency; Soft set theory; Association rules; Decision making
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Informatics & Computing
Depositing User: Syahmi Manaf
Date Deposited: 13 Sep 2022 04:44
Last Modified: 13 Sep 2022 04:44
URI: http://eprints.unisza.edu.my/id/eprint/7137

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