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Volumn 2006, Issue , 2006, Pages 4-13

Deriving quantitative models for correlation clusters

Author keywords

Cluster description; Cluster model; Clustering; Correlation clustering; Data mining

Indexed keywords

ALGORITHMS; DATA MINING; DATA REDUCTION; MATHEMATICAL MODELS; PROBABILITY DISTRIBUTIONS;

EID: 33749545528     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1150402.1150408     Document Type: Conference Paper
Times cited : (31)

References (25)
  • 10
    • 27544508838 scopus 로고    scopus 로고
    • Analyzing microarray data using quantitative association rules
    • E. Georgii, L. Richter, U. Rückert, and S. Kramer. Analyzing microarray data using quantitative association rules. Bioinformatics, 21(Suppl. 2):ii1-ii8, 2005.
    • (2005) Bioinformatics , vol.21 , Issue.2 SUPPL.
    • Georgii, E.1    Richter, L.2    Rückert, U.3    Kramer, S.4
  • 13
    • 0344464762 scopus 로고    scopus 로고
    • Sensitivity and specificity of inferring genetic regulatory interactions from microarray experiments with dynamic Bayesian networks
    • D. Husmeier. Sensitivity and specificity of inferring genetic regulatory interactions from microarray experiments with dynamic Bayesian networks. Bioinformatics, 19(17):2271-2282, 2003.
    • (2003) Bioinformatics , vol.19 , Issue.17 , pp. 2271-2282
    • Husmeier, D.1
  • 25
    • 0039926622 scopus 로고
    • The reduced row echelon form of a matrix is unique: A simple proof
    • T. Yuster. The reduced row echelon form of a matrix is unique: A simple proof. Mathematics Magazine, 57(2):93-94, 1984.
    • (1984) Mathematics Magazine , vol.57 , Issue.2 , pp. 93-94
    • Yuster, T.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.