Abstract
The estimation of convex sets when inside and outside observations are available is often needed in current research applications.
The key idea of this paper is to propose a solution based on convex and discriminant analysis tools, even when non convex domains are considered. Simulations are done and comparisons are made with respect to a natural candidate for estimation of non convex bodies, based on the Voronoi tessellation. A part of this paper is devoted to a theoretical framework showing how convex sets can be used to approximate non convex sets in IR 2.
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© 2002 Springer-Verlag Berlin Heidelberg
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Rémon, M. (2002). Convex Discriminant Analysis Tools for Non Convex Pattern Recognition. In: Gaul, W., Ritter, G. (eds) Classification, Automation, and New Media. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55991-4_17
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DOI: https://doi.org/10.1007/978-3-642-55991-4_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-43233-3
Online ISBN: 978-3-642-55991-4
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