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Volumn 5572 LNAI, Issue , 2009, Pages 195-202

An evolutionary algorithm for missing values substitution in classification tasks

Author keywords

Bioinformatics; Classification; Clustering; Missing Values

Indexed keywords

ALTERNATIVE APPROACH; BIOINFORMATICS DATA; CLASSIFICATION; CLASSIFICATION BIAS; CLASSIFICATION TASKS; CLUSTERING; EVOLUTIONARY ALGORITHM FOR CLUSTERING; IMPUTATION ALGORITHM; IMPUTATION METHODS; MISSING VALUES; MODELING TASK; PREDICTION CAPABILITY; STATE-OF-THE-ART ALGORITHMS;

EID: 70350638783     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-02319-4_23     Document Type: Conference Paper
Times cited : (2)

References (7)
  • 3
    • 34248557635 scopus 로고    scopus 로고
    • Improving cluster-based missing value estimation of dna microarray data
    • Brás, L.P., Menezes, J.C.: Improving cluster-based missing value estimation of dna microarray data. Biomolecular Engineering 24, 273-282 (2007)
    • (2007) Biomolecular Engineering , vol.24 , pp. 273-282
    • Brás, L.P.1    Menezes, J.C.2
  • 4
    • 13244298228 scopus 로고    scopus 로고
    • Reuse of imputed data in microarray analysis increases imputation efficiency
    • Kim, K.Y., Kim, B.J., Yi, G.S.: Reuse of imputed data in microarray analysis increases imputation efficiency. BMC Bioinformatics 5, 160 (2004)
    • (2004) BMC Bioinformatics , vol.5 , pp. 160
    • Kim, K.Y.1    Kim, B.J.2    Yi, G.S.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.