Algorithms for Regularized Linear Discriminant Analysis

Jan Kalina, Jurjen Duintjer Tebbens


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 regularized linear discriminant analysis, which exploits a regularized 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.


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Paper Citation

in Harvard Style

Kalina J. and Duintjer Tebbens J. (2015). Algorithms for Regularized Linear Discriminant Analysis . In Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2015) ISBN 978-989-758-070-3, pages 128-133. DOI: 10.5220/0005234901280133

in Bibtex Style

author={Jan Kalina and Jurjen Duintjer Tebbens},
title={Algorithms for Regularized Linear Discriminant Analysis},
booktitle={Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2015)},

in EndNote Style

JO - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2015)
TI - Algorithms for Regularized Linear Discriminant Analysis
SN - 978-989-758-070-3
AU - Kalina J.
AU - Duintjer Tebbens J.
PY - 2015
SP - 128
EP - 133
DO - 10.5220/0005234901280133