Application of Double Asymptotics and Random Matrix Theory in Error Estimation of Regularized Linear Discriminant Analysis Conference Paper uri icon

abstract

  • The theory of double asymptotics and random matrices has been employed to construct a nearly unbiased estimator of true error rate of linear discriminant analysis with ridge estimator of inverse covariance matrix in the multivariate Gaussian model. In such a scenario, the performance of the constructed estimator, as measured by Root-Mean-Square (RMS) error, shows improvement over well-known estimators of true error. 2013 IEEE.

name of conference

  • 2013 IEEE Global Conference on Signal and Information Processing

published proceedings

  • 2013 IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (GLOBALSIP)

author list (cited authors)

  • Zollanvari, A., & Dougherty, E. R.

citation count

  • 2

complete list of authors

  • Zollanvari, Amin||Dougherty, Edward R

publication date

  • December 2013