Regularized Discriminant Analysis

  title={Regularized Discriminant Analysis},
  author={J. Friedman},
  journal={Journal of the American Statistical Association},
  • J. Friedman
  • Published 1989
  • Mathematics
  • Journal of the American Statistical Association
  • Abstract Linear and quadratic discriminant analysis are considered in the small-sample, high-dimensional setting. Alternatives to the usual maximum likelihood (plug-in) estimates for the covariance matrices are proposed. These alternatives are characterized by two parameters, the values of which are customized to individual situations by jointly minimizing a sample-based estimate of future misclassification risk. Computationally fast implementations are presented, and the efficacy of the… CONTINUE READING
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