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Volumn 4756 LNCS, Issue , 2007, Pages 684-693

Modification of the growing neural gas algorithm for cluster analysis

Author keywords

Clustering; GNG; S P100; Vectorial quantization

Indexed keywords

CLUSTER ANALYSIS; PROBLEM SOLVING; TOPOLOGY; VECTOR QUANTIZATION;

EID: 38549167944     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: None     Document Type: Conference Paper
Times cited : (13)

References (13)
  • 1
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    • A neural gas network learns topology
    • Elsevier Science Publishers, Amsterdam, Holanda
    • Martinetz, T., Schulten, K.: A neural gas network learns topology. Artificial Neural Networks, pp. 397-402. Elsevier Science Publishers, Amsterdam, Holanda (1991)
    • (1991) Artificial Neural Networks , pp. 397-402
    • Martinetz, T.1    Schulten, K.2
  • 2
    • 0034187784 scopus 로고    scopus 로고
    • Clustering of the self-organizing map
    • Vesanto, J., Alhoniemi, E.: Clustering of the self-organizing map. IEEE 3, 11 (2000)
    • (2000) IEEE , vol.3 , pp. 11
    • Vesanto, J.1    Alhoniemi, E.2
  • 5
    • 0020068152 scopus 로고
    • Self-organized formation of topologically correct feature maps
    • Kohonen, T.: Self-organized formation of topologically correct feature maps. Biological Cybernetics 43, 59-69 (1982)
    • (1982) Biological Cybernetics , vol.43 , pp. 59-69
    • Kohonen, T.1
  • 6
    • 0027632248 scopus 로고
    • Neural gas network for vector quantization and its application to time
    • 4
    • Martinetz, T., Berkovich, S., Schulten, K.: Neural gas network for vector quantization and its application to time-series prediction. IEEE 4, 4, 218-226 (1993)
    • (1993) series prediction. IEEE , vol.4 , pp. 218-226
    • Martinetz, T.1    Berkovich, S.2    Schulten, K.3
  • 7
    • 0028748949 scopus 로고
    • Growing cell structures - a self-organizing network for unsupervised and supervised learning
    • Fritzke, B.: Growing cell structures - a self-organizing network for unsupervised and supervised learning. Neural Networks 1441-1460 (1994)
    • (1994) Neural Networks , pp. 1441-1460
    • Fritzke, B.1
  • 8
    • 0001132486 scopus 로고
    • Competitive hebbian learning rule forms perfectly topology preserving maps
    • Martinetz, T.: Competitive hebbian learning rule forms perfectly topology preserving maps. In: ICANN 1993, pp. 427-434 (1993)
    • (1993) ICANN 1993 , pp. 427-434
    • Martinetz, T.1
  • 10
    • 0017360990 scopus 로고
    • The measurement of observer agreement for categorical data
    • Landis, J.R., Koch, G.G.: The measurement of observer agreement for categorical data. Biometrics 33, 159-174 (1977)
    • (1977) Biometrics , vol.33 , pp. 159-174
    • Landis, J.R.1    Koch, G.G.2
  • 12
    • 0001237015 scopus 로고
    • Kohonen feature maps and growing cell structures - A performance comparison
    • Fritzke, B.: Kohonen feature maps and growing cell structures - A performance comparison. Advances in Neural Information Processing Systems 5, 115-122 (1993)
    • (1993) Advances in Neural Information Processing Systems , vol.5 , pp. 115-122
    • Fritzke, B.1
  • 13
    • 0041654220 scopus 로고
    • Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis
    • Kruskal, J.B.: Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis. Psychometrika 29, 1-27 (1964)
    • (1964) Psychometrika , vol.29 , pp. 1-27
    • Kruskal, J.B.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.