168687 20260213191050.0 sideral 75622 ART-2003-75622 eng Lozano, M. (orcid)0000-0003-0630-4366 Reducing Training Sets by NCN-based Exploratory Procedures 2003 In this paper, a new approach to training set size reduction is presented. This scheme basically consists of defining a small number of prototypes that represent all the original instances. Although the ultimate aim of the algorithm proposed here is to obtain a strongly reduced training set, the performance is empirically evaluated over nine real datasets by comparing not only the reduction rate but also the classification accuracy with those of other condensing techniques. Access copy available to the general public Unrestricted info:eu-repo/semantics/openAccess All rights reserved http://www.europeana.eu/rights/rr-f/ info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Sánchez, JS. Pla, F. 2652 (2003), 453-461 Lect. notes comput. sci. Lecture Notes in Computer Science 0302-9743 281104 http://zaguan.unizar.es/record/168687/files/texto_completo.pdf Postprint 1540705 http://zaguan.unizar.es/record/168687/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:168687 articulos driver 2026-02-13-18:28:29 ARTICLE