Computational models of the artificial intelligence such as rough set theory have several applications. Rough set-based data clustering can be considered further as a technique for medical decision making. This paper presents the results of an experimental study of a rough-set based clustering technique using Variable Precision Rough Set (VPRS). Here, we employ our proposed clustering technique [12] through a medical dataset of patients suspected diabetic. Our results indicate that the VPRS-based technique is better than that the standard rough set-based techniques in the process of selecting a clustering attribute.
목차
Abstract 1. Introduction 2. Variable Precision Rough Set 2.1. Set Approximations 2.2. Variable Precision Rough Set 3. Rough Set-based Techniques for Selecting a Clustering Attribute 4. Experiment Results 4.1. Material 4.2. Clustering problem 4.3. Result 4.4. Cluster purity and its visualization 5. Conclusion Acknowledgements References
Tutut Herawan [ Department of Mathematics Education, Universitas Ahmad Dahlan Jalan Prof Dr Soepomo 55166, Yogyakarta, Indonesia ]
Wan Maseri Wan Mohd [ Faculty of Computer System and Software Engineering Universiti Malaysia Pahang Lebuh Raya Tun Razak, Gambang 26300, Kuantan, Pahang, Malaysia ]
보안공학연구지원센터(IJMUE) [Science & Engineering Research Support Center, Republic of Korea(IJMUE)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Multimedia and Ubiquitous Engineering
간기
월간
pISSN
1975-0080
수록기간
2008~2016
등재여부
SCOPUS
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Multimedia and Ubiquitous Engineering Vol.9 No.1