Soft set approach for selecting decision attribute in data clustering

Authors:
Mohd Isa Awang;Ahmad Nazari Mohd Rose;Tutut Herawan;Mustafa Mat Deris
Affiliations:
Faculty of Informatics, Universiti Sultan Zainal Abidin, Terengganu, Malaysia;Faculty of Informatics, Universiti Sultan Zainal Abidin, Terengganu, Malaysia;Department of Mathematics Education, Universitas Ahmad Dahlan, Yogyakarta, Indonesia and Faculty of Information Technology and Multimedia, Universiti Tun Hussein Onn Malaysia, Johor, Malaysia;Faculty of Information Technology and Multimedia, Universiti Tun Hussein Onn Malaysia, Johor, Malaysia
Venue:
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications - Volume Part II
Year:
2010

Citing 3
Cited 1

The normal parameter reduction of soft sets and its algorithm

Computers & Mathematics with Applications
The parameterization reduction of soft sets and its applications

Computers & Mathematics with Applications
A rough set approach for selecting clustering attribute

Knowledge-Based Systems

The Position of Rough Set in Soft Set: A Topological Approach

International Journal of Applied Metaheuristic Computing

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Abstract

This paper presents the applicability of soft set theory for discovering a decision attribute in information systems. It is based on the notion of a mapping inclusion in soft set theory. The proposed technique is implemented with example test case and one UCI benchmark data; US Census 1990 dataset. The results from test case show that the selected decision attribute is equivalent to that under rough set theory.