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Titulo: A New Approach to the Extraction of ANN Rules and to their Generalization Capacity throught GP
Tipo: revista internacional
Fecha: 7,2004
Revista: Neural Computation
JCR Journal; Impact Factor: 2.364
Citas ISI: 9 Citas Scopus: 13 Citas Google Scholar: 17
Volumen: 16(7)
Paginas: 1483-1523
ISSN: 0899-7667
Editorial: MIT Press
Cambridge (UK)


Various techniques for the extraction of ANN rules have been used, but most of them have focused on certain types of networks and their training. There are very few methods that deal with ANN rule extraction as systems that are independent of their architecture, training, and internal distribution of weights, connections, and activation functions. This article proposes a methodology for the extraction of ANN rules, regardless of their architecture, and based on genetic programming. The strategy is based on the previous algorithm and aims at achieving the generalization capacity that is characteristic of ANNs by means of symbolic rules that are understandable to human beings.

    .: SABIA :.  Sistemas Adaptativos y Bioinspirados en Inteligencia Artificial