0431042 - ÚI 2015 RIV CH eng C - Conference Paper (international conference)
Kalina, Jan - Valenta, Zdeněk - Duintjer Tebbens, Jurjen
Computation of Regularized Linear Discriminant Analysis.
Proceedings of COMPSTAT 2014. Geneva: Centre International de Conferences, 2014 - (Gilli, M.; Nieto-Reyes, A.; González-Rodríguez, G.), s. 1-8. ISBN 978-2-8399-1347-8.
[COMPSTAT 2014. International Conference on Computational Statistics /21./. Geneva (CH), 19.08.2014-22.08.2014]
R&D Projects: GA ČR GA13-06684S
Institutional support: RVO:67985807
Keywords : classification analysis * regularization * Matrix decomposition * shrinkage eigenvalues * high-dimensional data
Subject RIV: BB - Applied Statistics, Operational Research

This paper is focused on regularized versions of classification analysis and their computation for high-dimensional data. A variety of regularized classification methods has been proposed and we critically discuss their computational aspects. We formulate several new algorithms for shrinkage linear discriminant analysis, which exploits a shrinkage covariance matrix estimator towards a regular target matrix. Numerical linear algebra considerations are used to propose tailor-made algorithms for specific choices of the target matrix. Further, we arrive at proposing a new classification method based on L2-regularization of group means and the pooled covariance matrix and accompany it by an efficient algorithm for its computation.
Permanent Link: http://hdl.handle.net/11104/0235685