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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/8657

    Title: A novel classifier for influenza A viruses based on SVM and logistic regression
    Authors: Liu, Hsiang-Chuan;Liu, Shin-Wu;Chang, Pei-Chun;Huang, Wen-Chun;Liao, Chien-Hsiung
    Contributors: Department of Bioinformatics
    Keywords: Classifiers;Feature extraction;Learning systems;Logistics;Microorganisms;Pattern recognition;Support vector machines;Viruses;Wavelet analysis;Wavelet transforms;Hurst exponent;Influenza A viruses;Logistic regression;SVM;SVM-Logistic regression
    Date: 2008
    Issue Date: 2010-04-07 21:21:21 (UTC+8)
    Publisher: Asia University
    Abstract: In search of good classifier of hosts of influenza A viruses is an important issue to prevent pandemic flu. The hemagglutinin protein in the virus genome is the major molecule that determining the range of hosts. In this paper, a novel classification algorithm of hemagglutinin proteins integrating SVM and logistic regression based on 4 kinds of Hurst exponents for each protein sequence is proposed. This method not used before is the first one integrating the physicochemical properties, fractal property, SVM and logistic regression classifier. For evaluating the performance of this new algorithm, a real data experiment by using 5-fold Cross-Validation accuracy is conducted. Experimental result shows that this new classification algorithm is useful and batter than SVM and logistic regression, respectively. ©2008 IEEE.
    Relation: Proceedings of the 2008 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR 1 :287-291
    Appears in Collections:[生物資訊與醫學工程學系 ] 期刊論文

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