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Volumn 23, Issue 2, 2010, Pages 144-149

G-ANMI: A mutual information based genetic clustering algorithm for categorical data

Author keywords

Categorical data; Cluster ensemble; Clustering; Data mining; Genetic algorithm; Mutual information

Indexed keywords

CATEGORICAL DATA; CATEGORICAL DATA CLUSTERING; CLUSTERING ACCURACY; GENETIC CLUSTERING ALGORITHMS; KEY PROBLEMS; MUTUAL INFORMATIONS; NORMALIZED MUTUAL INFORMATION; OPTIMAL PARTITIONS; OPTIMIZATION PROBLEMS;

EID: 75849147143     PISSN: 09507051     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.knosys.2009.11.001     Document Type: Article
Times cited : (46)

References (12)
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  • 3
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    • A cluster ensemble method for clustering categorical data
    • He Z., Xu X., and Deng S. A cluster ensemble method for clustering categorical data. Information Fusion 6 2 (2005) 143-151
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    • He, Z.1    Xu, X.2    Deng, S.3
  • 5
    • 0041965980 scopus 로고    scopus 로고
    • Cluster ensembles-a knowledge reuse framework for combining multiple partitions
    • Strehl A., and Ghosh J. Cluster ensembles-a knowledge reuse framework for combining multiple partitions. Journal of Machine Learning Research 3 (2002) 583-617
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    • Strehl, A.1    Ghosh, J.2
  • 7
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    • TCSOM: clustering transactions using self-organizing map
    • He Z., Xu X., and Deng S. TCSOM: clustering transactions using self-organizing map. Neural Processing Letters 22 3 (2005) 249-262
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    • He, Z.1    Xu, X.2    Deng, S.3
  • 11
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    • Squeezer: an efficient algorithm for clustering categorical data
    • He Z., Xu X., and Deng S. Squeezer: an efficient algorithm for clustering categorical data. Journal of Computer Science and Technology 17 5 (2002) 611-624
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.