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.engHill ClimbersFeature SelectionTypical TestorsPattern Recognitioninfo:eu-repo/semantics/article