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Volumn 4578 LNAI, Issue , 2007, Pages 219-226

Possibilistic clustering in feature space

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING ALGORITHMS; MATHEMATICAL MODELS;

EID: 37249066212     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-73400-0_27     Document Type: Conference Paper
Times cited : (2)

References (12)
  • 1
    • 0000874557 scopus 로고
    • Theoretical foundations of the potential function method in pattern recognition learning
    • Aizerman, M., Braverman, E., Rozonoer, L.: Theoretical foundations of the potential function method in pattern recognition learning. Automation and Remote Control 25, 821-837 (1964)
    • (1964) Automation and Remote Control , vol.25 , pp. 821-837
    • Aizerman, M.1    Braverman, E.2    Rozonoer, L.3
  • 6
    • 0030214781 scopus 로고    scopus 로고
    • The possibilistic c-means algorithm: Insights and recommendations
    • Krishnapuram, R., Keller, J.M.: The possibilistic c-means algorithm: insights and recommendations. IEEE Transactions on Fuzzy Systems 4(3), 385-393 (1996)
    • (1996) IEEE Transactions on Fuzzy Systems , vol.4 , Issue.3 , pp. 385-393
    • Krishnapuram, R.1    Keller, J.M.2
  • 7
    • 26944437870 scopus 로고    scopus 로고
    • Mizutani, K., Miyamoto, S.: Possibilistic Approach to Kernel-Based Fuzzy c-Means Clustering with Entropy Regularization. In: Torra, V., Narukawa, Y., Miyamoto, S. (eds.) MDAI 2005. LNCS (LNAI), 3558, pp. 144-155. Springer, Heidelberg (2005)
    • Mizutani, K., Miyamoto, S.: Possibilistic Approach to Kernel-Based Fuzzy c-Means Clustering with Entropy Regularization. In: Torra, V., Narukawa, Y., Miyamoto, S. (eds.) MDAI 2005. LNCS (LNAI), vol. 3558, pp. 144-155. Springer, Heidelberg (2005)
  • 10
    • 33847214558 scopus 로고    scopus 로고
    • Possibilistic Fuzzy c-Means Clustering Model Using Kernel Methods. Proceedings of the Int. Conf. Computational Intelligence for Modelling
    • Web Technologies and Internet Commerce
    • Wu, X.H., Zhou, J.-J.: Possibilistic Fuzzy c-Means Clustering Model Using Kernel Methods. Proceedings of the Int. Conf. Computational Intelligence for Modelling, Control and Automation and Int. Conf.Intelligent Agents, Web Technologies and Internet Commerce, vol. 2, pp. 465-470 (2005)
    • (2005) Control and Automation and Int. Conf.Intelligent Agents , vol.2 , pp. 465-470
    • Wu, X.H.1    Zhou, J.-J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.