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Volumn 7, Issue 10, 2015, Pages 122-128

Multidimensional data classification based on BP neural network algorithm

Author keywords

BP neural network; Cloud computing; Data classification; Internet of things; Multi dimensional data

Indexed keywords

ALGORITHMS; CLOUD COMPUTING; DISTRIBUTED COMPUTER SYSTEMS; INTERNET; INTERNET OF THINGS; NEURAL NETWORKS;

EID: 84960074849     PISSN: 20760507     EISSN: 20788312     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (6)

References (12)
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    • Multi-class pattern classification using neural networks
    • Ou G., Murphey Y. (2007) Multi-class pattern classification using neural networks. Pattern Recognition, 47(1), p.p. 4-18.
    • (2007) Pattern Recognition , vol.47 , Issue.1 , pp. 4-18
    • Ou, G.1    Murphey, Y.2
  • 2
    • 85008039450 scopus 로고    scopus 로고
    • Online sequential fizzy extreme learning machine for function approximation and classification problems
    • Rong H.J., Huang G.B. (2009) Online sequential fizzy extreme learning machine for function approximation and classification problems. IEEE Transactions on Systems, Man and Cybernetics-Part B, 42(4), p.p. 1067-1072.
    • (2009) IEEE Transactions on Systems, Man and Cybernetics-Part B , vol.42 , Issue.4 , pp. 1067-1072
    • Rong, H.J.1    Huang, G.B.2
  • 4
    • 69549133517 scopus 로고    scopus 로고
    • Measuring classifier performance:A coherent alternative to the area under the ROC curve
    • Hand D.J. (2009) Measuring classifier performance:A coherent alternative to the area under the ROC curve. Machine Learning, 80(1), p.p. 103-123.
    • (2009) Machine Learning , vol.80 , Issue.1 , pp. 103-123
    • Hand, D.J.1
  • 5
    • 33646023117 scopus 로고    scopus 로고
    • An introduction to ROC analysis
    • Fawcett T. (2005) An introduction to ROC analysis. Pattern Recognition Letters, 33(8), p.p.861-874.
    • (2005) Pattern Recognition Letters , vol.33 , Issue.8 , pp. 861-874
    • Fawcett, T.1
  • 6
    • 27144531570 scopus 로고    scopus 로고
    • A study of the behavior of several methods for balancing machine learning training data
    • Batista G.E., Prati R.C., Monard M.C. (2004) A study of the behavior of several methods for balancing machine learning training data. ACM SIGKDD Explorations Newsletter, 12(1), p.p.20-29.
    • (2004) ACM SIGKDD Explorations Newsletter , vol.12 , Issue.1 , pp. 20-29
    • Batista, G.E.1    Prati, R.C.2    Monard, M.C.3
  • 7
    • 3142747654 scopus 로고    scopus 로고
    • Neural learning from unbalanced data
    • Murphey Y.L., Guo H., Feldkamp L. (2004) Neural learning from unbalanced data. Applied Intelligence, 31(2), p.p. 117-128.
    • (2004) Applied Intelligence , vol.31 , Issue.2 , pp. 117-128
    • Murphey, Y.L.1    Guo, H.2    Feldkamp, L.3
  • 10
    • 0036555952 scopus 로고    scopus 로고
    • Influences of variable scales and activation functions on the performances of multilayer feedforward neural networks
    • Gao D.Q., Yang G.X. (2003) Influences of variable scales and activation functions on the performances of multilayer feedforward neural networks. Pattern Recognition, 43(4), p.p. 869-878.
    • (2003) Pattern Recognition , vol.43 , Issue.4 , pp. 869-878
    • Gao, D.Q.1    Yang, G.X.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.