On the crossover operator for Ga-based optimizers in sequential projection pursuit

Soledad Espezua, Edwin Villanueva, Carlos D. Maciel

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

Sequential Projection Pursuit (SPP) is a useful tool to uncover structures hidden in high-dimensional data by constructing sequentially the basis of a low-dimensional projection space where the structure is exposed. Genetic algorithms (GAs) are promising finders of optimal basis for SPP, but their performance is determined by the choice of the crossover operator. It is unknown until now which operator is more suitable for SPP. In this paper we compare, over four public datasets, the performance of eight crossover operators: three available in literature (arithmetic, single-point and multi-point) and five new proposed here (two hyperconic, two fitness-biased and one extension of arithmetic crossover). The proposed hyperconic operators and the multi-point operator showed the best performance, finding high-fitness projections. However, it was noted that the final selection is dependent on the dataset dimension and the timeframe allowed to get the answer. Some guidelines to select the most appropriate operator for each situation are presented.

Idioma originalInglés
Título de la publicación alojadaICPRAM 2012 - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods
EditorialSciTePress
Páginas93-102
Número de páginas10
ISBN (versión impresa)978-989-8425-98-0
EstadoPublicada - 2012
Publicado de forma externa
Evento1st International Conference on Pattern Recognition Applications and Methods, ICPRAM 2012 - Vilamoura, Algarve, Portugal
Duración: 6 feb. 20128 feb. 2012

Conferencia

Conferencia1st International Conference on Pattern Recognition Applications and Methods, ICPRAM 2012
País/TerritorioPortugal
CiudadVilamoura, Algarve
Período6/02/128/02/12

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