Numerous studies have focused on feature selection using many algorithms, but most of these algorithms encounter problems when the amount of data is large. In this paper, we propose an algorithm that handles a large amount of data by partitioning the data to process a reduction, and then selecting the intersection of all reducts as a stable reduct. This algorithm is successful but may suffer from loss of information if the samples are unsuitable. The proposed algorithm is based on discernibility matrix and function. Furthermore, the method can address the case in which the data consist of a significant amount of information. Our results show that the proposed algorithm is powerful and flexible enough to successfully target a range of different domains and can effectively reduce computational complexity as well as increase reduction efficiency. The efficiency of Proposed Algorithm is illustrated by experiments with UCI datasets further.
목차
Abstract 1. Introduction 2. Related Work 3. Rough Set Base Approach 3.1. Information System and Indiscernibility Relation 3.2. Class Approximation 3.3. Dispensable and Indispensable Features 3.4. Reduct and CORE 3.4. The Discernibility Matrix and the Discernibility Function 4. Minimal Attribute Reduction Based on Discernibility Function 5. Feature Selection Using Rough Set 6. Selection Minimal Attributes Reduction 6.1. Proposed Algorithm 6.2. How Does The Algorithm Work? 6.3. Illustrative Example 7. Algorithm Testing and Comparison (Implementation) 8. Conclusion References
키워드
Rough set algorithmMinimal attributes reductionPartition algorithmReduct and Core
저자
Khaled Alwesabi [ School of Information Science and Engineering, Central South University Changsha, Hunan (HN), 410000/ Time (UTC+8), China ]
Corresponding author
Weihua Gui [ School of Information Science and Engineering, Central South University Changsha, Hunan (HN), 410000/ Time (UTC+8), China ]
Chunhua Yang [ School of Information Science and Engineering, Central South University Changsha, Hunan (HN), 410000/ Time (UTC+8), China ]
Hamdi Rajeh [ Hunan University, Changsha, Hunan, China ]
보안공학연구지원센터(IJHIT) [Science & Engineering Research Support Center, Republic of Korea(IJHIT)]
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 Hybrid Information Technology
간기
격월간
pISSN
1738-9968
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Hybrid Information Technology Vol.9 No.8