Proceedings of the Korean Institute of Intelligent Systems Conference (한국지능시스템학회:학술대회논문집)
- 2000.05a
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- Pages.94-97
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- 2000
Approximate fuzzy clustering based on a density function
밀도 함수를 이용한 근사적 퍼지 클러스터링
Abstract
We introduce an approximate fuzzy clustering method, which is simple but computationally efficient, based on density functions in this paper. The density functions are defined by the number of data within the predetermined interval. Numerical examples are presented to show the validity of the proposed clustering method.
Keywords