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    Please use this identifier to cite or link to this item: http://nthur.lib.nthu.edu.tw/dspace/handle/987654321/12695


    Title: Bootstrap Techniques for Error Estimation
    Authors: Jain, A.K.
    Dubes, R.C.
    Chen, C.-C.
    教師: 陳朝欽
    Date: 1987
    Relation: IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, Volume: 9, Issue 5, Page(s):628-633
    Keywords: Pattern recognition
    Classifier
    Error estimation
    System performance
    Decision rule
    Nearest neighbour
    Quadratic system
    Abstract: The authors report results on the application of several bootstrap techniques in estimating the error rate of nearest-neighbor (1-NN) and quadratic classifiers. The conducted experiments show that, in most cases, the confidence interval of a bootstrap estimator of classification error is smaller than that of the leave-one-out estimator. The error of 1-NN, quadratic, and Fisher classifiers are estimated for several real data sets
    Relation Link: http://ieeexplore.ieee.org/Xplore/dynhome.jsp
    URI: http://nthur.lib.nthu.edu.tw/handle/987654321/12695
    Appears in Collections:[資訊工程學系] 期刊論文
    [資訊系統與應用研究所] 期刊論文

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