Sánchez-Díaz, GuillermoDíaz-Sánchez, GermánMora-González, MiguelAguirre-Salado, Carlos A.Huerta-Cuéllar, GuillermoPiza-Dávila, Hugo I.Reyes-Cárdenas, ÓscarCárdenas-Tristán, Abraham2014-03-142014-03-142014-05-01Sanchez-Diaz, G.; Diaz-Sanchez, G.; Mora-Gonzalez, M; Piza-Davila, H.I.; Aguirre-Salado, C.A.; Huerta-Cuellar, G; Reyes-Cardenas, O.; Cardenas-Tristan, A. (2014). "An evolutionary algorithm with acceleration operator to generate a subset of typical testors". Pattern Recognition Letters. Volume 41, 1 May, pp.34-42.0167-8655http://www.sciencedirect.com/science/article/pii/S0167865513004297http://hdl.handle.net/11117/1217This paper is focused on introducing a Hill-Climbing algorithm as a way to solve the problem of generating typical testors – or non-reducible descriptors – from a training matrix. All the algorithms reported in the state-of-the-art have exponential complexity. However, there are problems for which there is no need to generate the whole set of typical testors, but it suffices to find only a subset of them. For this reason, we introduce a Hill-Climbing algorithm that incorporates an acceleration operation at the mutation step, providing a more efficient exploration of the search space. The experiments have shown that, under the same circumstances, the proposed algorithm performs better than other related algorithms reported so far.enghttp://quijote.biblio.iteso.mx/licencias/CC-BY-NC-2.5-MX.pdfHill ClimbersFeature SelectionTypical TestorsPattern Recognitioninfo:eu-repo/semantics/article