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Volumn 12, Issue 1, 2003, Pages 42-48

Application of self-organising maps for data mining with incomplete data sets

Author keywords

Fuzzy clustering; Incomplete data; Self organising maps

Indexed keywords

ARTIFICIAL INTELLIGENCE; DATA MINING; DATABASE SYSTEMS; FUZZY SETS; KNOWLEDGE BASED SYSTEMS;

EID: 0141904587     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00521-003-0372-1     Document Type: Article
Times cited : (56)

References (13)
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  • 2
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  • 4
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    • UK: Springer-Verlag
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    • Deboeck, G.1    Kohonen, T.2
  • 5
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    • Fuzzy self-organizing map
    • Vuorimaa P (1994) Fuzzy self-organizing map. Fuzzy Sets and Systems 66:223-231
    • (1994) Fuzzy Sets and Systems , vol.66 , pp. 223-231
    • Vuorimaa, P.1
  • 7
    • 0004008854 scopus 로고
    • Pattern recognition with fuzzy objective function algorithms
    • New York: Plenum Press
    • Bezdek JC (1981) Pattern recognition with fuzzy objective function algorithms. New York: Plenum Press
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    • Bezdek, J.C.1
  • 8
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    • A fuzzy relative of the ISODATA process and its use in detecting compact well separated clusters
    • Dunn JC (1973) A fuzzy relative of the ISODATA process and its use in detecting compact well separated clusters. J Cybernetics 3(3):32-57
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  • 9
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    • Statistical analysis with missing data
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  • 10
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    • Maximum likelihood from incomplete data via the EM algorithm
    • Dempster AP, Laird NM, Rubin DB (1997) Maximum likelihood from incomplete data via the EM algorithm. J Royal Statis Soc B39(1):1-38
    • (1997) J Royal Statis Soc , vol.B39 , Issue.1 , pp. 1-38
    • Dempster, A.P.1    Laird, N.M.2    Rubin, D.B.3
  • 11
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    • Clustering algorithms
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  • 12
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    • Fuzzy sets as a basis for a theory of possibility
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.