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Volumn 25, Issue 1, 2012, Pages 22-34

Class imbalance methods for translation initiation site recognition in DNA sequences

Author keywords

Bioinformatics; Classification; Gene recognition; Imbalance datasets; Translation initiation site recognition

Indexed keywords

BIOLOGICAL CHARACTERISTIC; CDNA SEQUENCE; CLASS IMBALANCE; CLASS IMBALANCE PROBLEMS; CLASSIFICATION ALGORITHM; CLASSIFICATION METHODS; DATA MINING ALGORITHM; DATA SETS; GENE RECOGNITION; GENE STRUCTURE PREDICTION; IMBALANCED DATA-SETS; MEMORY REQUIREMENTS; SCALING-UP; TRAINING TIME; TRANSLATION INITIATION SITE; TRANSLATION INITIATION SITE RECOGNITION; UNDER-SAMPLING;

EID: 80052415991     PISSN: 09507051     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.knosys.2011.05.002     Document Type: Article
Times cited : (82)

References (28)
  • 1
    • 10044283330 scopus 로고    scopus 로고
    • Using amino acid patterns to accurately predict translation initiation sites
    • H. Liu, H. Han, J. Li, and L. Wong Using amino acids patterns to accurately predict translation initiation sites Silico Biology 4 2004 255 269 (Pubitemid 39600475)
    • (2004) Silico Biology , vol.4 , Issue.3 , pp. 255-269
    • Liu, H.1    Han, H.2    Li, J.3    Wong, L.4
  • 2
    • 34547852234 scopus 로고    scopus 로고
    • Translation initiation site prediction on a genomic scale: Beauty in simplicity
    • Y. Saeys, T. Abeel, S. Degroeve, and Y.V. de Peer Translation initiation site prediction on a genomic scale: beauty in simplicity Bioinformatics 23 2007 418 423
    • (2007) Bioinformatics , vol.23 , pp. 418-423
    • Saeys, Y.1    Abeel, T.2    Degroeve, S.3    De Peer, Y.V.4
  • 4
    • 54949132937 scopus 로고    scopus 로고
    • A comparative study on rough set based class imbalance learning
    • J. Liu, Q. Hu, and D. Yu A comparative study on rough set based class imbalance learning Knowledge-Based Systems 21 2008 753 763
    • (2008) Knowledge-Based Systems , vol.21 , pp. 753-763
    • Liu, J.1    Hu, Q.2    Yu, D.3
  • 6
    • 34547673383 scopus 로고    scopus 로고
    • Cost-sensitive boosting for classification of imbalanced data
    • DOI 10.1016/j.patcog.2007.04.009, PII S0031320307001835
    • Y. Sun, M.S. Kamel, A.K.C. Wong, and Y. Wang Cost-sensitive boosting for classification of imbalanced data Pattern Recognition 40 2007 3358 3378 (Pubitemid 47223287)
    • (2007) Pattern Recognition , vol.40 , Issue.12 , pp. 3358-3378
    • Sun, Y.1    Kamel, M.S.2    Wong, A.K.C.3    Wang, Y.4
  • 7
    • 70349617264 scopus 로고    scopus 로고
    • Evolutionary undersampling for classification with imbalanced datasets: Proposals and taxonomy
    • S. García, and F. Herrera Evolutionary undersampling for classification with imbalanced datasets: Proposals and taxonomy Evolutionary Computation 17 3 2009 275 306
    • (2009) Evolutionary Computation , vol.17 , Issue.3 , pp. 275-306
    • García, S.1    Herrera, F.2
  • 11
    • 1442356040 scopus 로고    scopus 로고
    • A multiple resampling method for learning from imbalanced data sets
    • A. Estabrooks, T. Jo, and N. Japkowicz A multiple resampling method for learning from imbalanced data sets Computational Intelligence 20 1 2004 18 36
    • (2004) Computational Intelligence , vol.20 , Issue.1 , pp. 18-36
    • Estabrooks, A.1    Jo, T.2    Japkowicz, N.3
  • 14
    • 0032645080 scopus 로고    scopus 로고
    • An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants
    • E. Bauer, and R. Kohavi An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants Machine Learning 36 1/2 1999 105 142
    • (1999) Machine Learning , vol.36 , Issue.1-2 , pp. 105-142
    • Bauer, E.1    Kohavi, R.2
  • 15
    • 34250080806 scopus 로고
    • A weighted nearest neighbor algorithm for learning with symbolic features
    • S. Cost, and S. Salzberg A weighted nearest neighbor algorithm for learning with symbolic features Machine Learning 10 1 1993 57 78
    • (1993) Machine Learning , vol.10 , Issue.1 , pp. 57-78
    • Cost, S.1    Salzberg, S.2
  • 17
    • 0031998121 scopus 로고    scopus 로고
    • Machine learning for the detection of oil spills in satellite radar images
    • M. Kubat, R. Holte, and S. Matwin Machine learning for the detection of oil spills in satellite radar images Machine Learning 30 1998 195 215
    • (1998) Machine Learning , vol.30 , pp. 195-215
    • Kubat, M.1    Holte, R.2    Matwin, S.3
  • 18
    • 0034726260 scopus 로고    scopus 로고
    • Noisy replication in skewed binary classification
    • S. Lee Noisy replication in skewed binary classification Computational Statistics and Data Analysis 34 2000 165 191
    • (2000) Computational Statistics and Data Analysis , vol.34 , pp. 165-191
    • Lee, S.1
  • 24
    • 67349220171 scopus 로고    scopus 로고
    • Boosting k-nearest neighbor classifier by means of input space projection
    • N. García-Pedrajas, and D. Ortiz-Boyer Boosting k-nearest neighbor classifier by means of input space projection Expert Systems with Applications 36 7 2009 10570 10582
    • (2009) Expert Systems with Applications , vol.36 , Issue.7 , pp. 10570-10582
    • García-Pedrajas, N.1    Ortiz-Boyer, D.2
  • 25
    • 33749251505 scopus 로고    scopus 로고
    • A cooperative constructive method for neural networks for pattern recognition
    • N. García-Pedrajas, and D. Ortiz-Boyer A cooperative constructive method for neural networks for pattern recognition Pattern Recognition 40 1 2007 80 99
    • (2007) Pattern Recognition , vol.40 , Issue.1 , pp. 80-99
    • García-Pedrajas, N.1    Ortiz-Boyer, D.2
  • 27
    • 0042847140 scopus 로고    scopus 로고
    • Inference for the generalization error
    • C. Nadeau, and Y. Bengio Inference for the generalization error Machine Learning 52 2003 239 281
    • (2003) Machine Learning , vol.52 , pp. 239-281
    • Nadeau, C.1    Bengio, Y.2
  • 28
    • 0033670134 scopus 로고    scopus 로고
    • Engineering support vector machines kernels that recognize translation initiation sites
    • A. Zien, G. Rätsch, S. Mika, B. Schölkopf, T. Lengauer, and K.-R. Müller Engineering support vector machines kernels that recognize translation initiation sites Bioinformatics 16 9 2000 799 807
    • (2000) Bioinformatics , vol.16 , Issue.9 , pp. 799-807
    • Zien, A.1    Rätsch, G.2    Mika, S.3    Schölkopf, B.4    Lengauer, T.5    Müller, K.-R.6


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.