info:eu-repo/semantics/article
An evolutionary algorithm with acceleration operator to generate a subset of typical testors
Registro en:
Sanchez-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.
0167-8655
Autor
Sánchez-Díaz, Guillermo
Díaz-Sánchez, Germán
Mora-González, Miguel
Aguirre-Salado, Carlos A.
Huerta-Cuéllar, Guillermo
Piza-Dávila, Hugo I.
Reyes-Cárdenas, Óscar
Cárdenas-Tristán, Abraham
Institución
Resumen
This 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. ITESO, A.C.