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Linear discrimination with equicorrelated training vectors

  • Leiva, Ricardo
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    Fisher's linear discrimination rule requires uncorrelated training vectors. In this paper a linear discrimination method is developed to be used when the training vectors are equicorrelated. Also, maximum likelihood ratio tests are proposed to decide whether the training samples are uncorrelated or equicorrelated.

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    File URL: http://www.sciencedirect.com/science/article/B6WK9-4KPX8PH-1/2/dc0b507bbd88ae83c1460d00fff6a6aa
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    Article provided by Elsevier in its journal Journal of Multivariate Analysis.

    Volume (Year): 98 (2007)
    Issue (Month): 2 (February)
    Pages: 384-409

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    Handle: RePEc:eee:jmvana:v:98:y:2007:i:2:p:384-409
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    1. Paranjpe, S. A. & Gore, A. P., 1994. "Selecting variables for discrimination when covariance matrices are unequal," Statistics & Probability Letters, Elsevier, vol. 21(5), pages 417-419, December.
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