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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국정보처리학회 JIPS(Journal of Information Processing Systems) JIPS(Journal of Information Processing Systems) 제15권 제2호
- 발행연도
- 2019.1
- 수록면
- 359 - 373 (15page)
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초록· 키워드
오류제보하기
For clustering large-scale data, which cannot be loaded into memory entirely, incremental clustering algorithmsare very popular. Usually, these algorithms only concern the within-cluster compactness and ignore thebetween-cluster separation. In this paper, we propose two incremental fuzzy compactness and separation (FCS)clustering algorithms, Single-Pass FCS (SPFCS) and Online FCS (OFCS), based on a fuzzy scatter matrix. Firstly, we introduce two incremental clustering methods called single-pass and online fuzzy C-meansalgorithms. Then, we combine these two methods separately with the weighted fuzzy C-means algorithm, sothat they can be applied to the FCS algorithm. Afterwards, we optimize the within-cluster matrix and betweenclustermatrix simultaneously to obtain the minimum within-cluster distance and maximum between-clusterdistance. Finally, large-scale datasets can be well clustered within limited memory. We implemented experimentson some artificial datasets and real datasets separately. And experimental results show that, compared withSPFCM and OFCM, our SPFCS and OFCS are more robust to the value of fuzzy index m and noise.
목차
등록된 정보가 없습니다.
참고문헌 (21)
참고문헌 신청
Y. Liu / 2016 / Information bottleneck based incremental fuzzy clustering for large biomedical data / Journal of Biomedical Informatics 62:48~58
A. K. Jain / 2009 / Data clustering: 50 years beyond K-means / Pattern Recognition Letters 31(8):651~666
J. C. Bezdek / 1984 / FCM: the fuzzy c-means clustering algorithm / Computers &Geosciences 10(2-3):191~203
Y. Zhou / 2015 / A clustering algorithm based on feature weighting fuzzy compactness and separation / Algorithms 8(2):128~143
K. L. Wu / 2005 / A novel fuzzy clustering algorithm based on a fuzzy scatter matrix with optimality tests / Pattern Recognition Letters 26(5):639~652
A. K. Jain / 2009 / Data clustering: 50 years beyond K-means / Pattern Recognition Letters 31(8):651~666
J. C. Bezdek / 1984 / FCM: the fuzzy c-means clustering algorithm / Computers &Geosciences 10(2-3):191~203
Y. Zhou / 2015 / A clustering algorithm based on feature weighting fuzzy compactness and separation / Algorithms 8(2):128~143
K. L. Wu / 2005 / A novel fuzzy clustering algorithm based on a fuzzy scatter matrix with optimality tests / Pattern Recognition Letters 26(5):639~652
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