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Improvement on Fuzzy C-Means Using Principal Component AnalysisImprovement on Fuzzy C-Means Using Principal Component Analysis
- Other Titles
- Improvement on Fuzzy C-Means Using Principal Component Analysis
- Issue Date
- Apr-2006
- Publisher
- 한국데이터정보과학회
- Keywords
- Clustering; Fuzzy c-means; Principal component analysis
- Citation
- 한국데이터정보과학회지, v.17, no.2, pp.301 - 309
- Indexed
- KCI
- Journal Title
- 한국데이터정보과학회지
- Volume
- 17
- Number
- 2
- Start Page
- 301
- End Page
- 309
- ISSN
- 1598-9402
- Abstract
- In this paper, we show the improved fuzzy c-means clustering method. To improve, we use the double clustering as principal component analysis from objects which is located on common region of more than two clusters. In addition we use the degree of membership (probability) of fuzzy c-means which is the advantage. From simulation result, we find some improvement of accuracy in data of the probability 0.7 exterior and interior of overlapped area.
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Related Researcher
- Cha, Kyung Joon
- COLLEGE OF NATURAL SCIENCES (DEPARTMENT OF MATHEMATICS)