Artículo
A Two-Stage Algorithm in Evolutionary Product Unit Neural Networks for Classification
Autor/es | Tallón Ballesteros, Antonio Javier
Hervás Martínez, César |
Departamento | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos |
Fecha de publicación | 2011-01 |
Fecha de depósito | 2024-02-12 |
Publicado en |
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Resumen | This paper presents a procedure to add broader diversity at the beginning of the evolutionary process. It consists of creating two initial populations with different parameter settings, evolving them for a small number of ... This paper presents a procedure to add broader diversity at the beginning of the evolutionary process. It consists of creating two initial populations with different parameter settings, evolving them for a small number of generations, selecting the best individuals from each population in the same proportion and combining them to constitute a new initial population. At this point the main loop of an evolutionary algorithm is applied to the new population. The results show that our proposal considerably improves both the efficiency of previous methodologies and also, significantly, their efficacy in most of the data sets. We have carried out our experimentation on twelve data sets from the UCI repository and two complex real-world problems which differ in their number of instances, features and classes. |
Agencias financiadoras | Ministerio de Ciencia Y Tecnología (MCYT). España European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER) Junta de Andalucía |
Identificador del proyecto | TIN2007-68084-C02-02
TIN2008-06681-C06-03 P08-TIC-3745 |
Cita | Tallón Ballesteros, A.J. y Hervás Martínez, C. (2011). A Two-Stage Algorithm in Evolutionary Product Unit Neural Networks for Classification. Expert Systems with Applications, 38 (1), 743-754. https://doi.org/https://doi.org/10.1016/j.eswa.2010.07.028. |
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Paper ESWA 2011.pdf | 532.1Kb | [PDF] | Ver/ | Versión aceptada |