engLozano, M.Sotoca, JM.Sánchez, JS.Pla, F.An Adaptive Condensing Algorithm based on Mixtures of GaussiansART-2004-75695In this paper, a new adaptive approach to training set size reduction, estimating probability density functions is presented. This scheme consists of defining a very small number of prototypes that represent all the original instances, using mixtures of gaussians. Although the ultimate aim of the algorithm proposed here is to obtain a strongly reduced training set, the performance is empirically evaluated over eleven real datasets by comparing not only the reduction rate but also the classification accuracy2004http://zaguan.unizar.es/record/168685http://zaguan.unizar.es/record/168685oai:zaguan.unizar.es:168685Frontiers in Artificial Intelligence and Applications 113 (2004), 225-232All rights reservedhttp://www.europeana.eu/rights/rr-f/info:eu-repo/semantics/openAccess