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An improvement to the classification based on the measurement of the similarity quality using fuzzy relations

Fernandez Hernandez, Yumilka Barbara and Filiberto, Yaima and Frias, Mabel and Bello, Rafael and Caballero, Yaile (2015) An improvement to the classification based on the measurement of the similarity quality using fuzzy relations. DYNA, 82 (193). pp. 70-76. ISSN 2346-2183

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Resumen

The learning of classification rules is a classic problem of the automatic learning. The algorithm IRBASIR for the induction of classification rules based on similaridad relations allows to discover knowledge starting from decision systems that contain features with continuous and discrete domains. This algorithm has shown to obtain higher results than other well-known algorithms. In this article, several modifications to this algorithm based on the Fuzzy sets theory are proposed, taking into account the measure quality of similarity. The experimental results show that using the fuzzy sets theory allow to obtain higher results than the original algorithm.

Tipo de documento:Artículo - Article
Palabras clave:classification rules, fuzzy sets, similarity relations
Temática:6 Tecnología (ciencias aplicadas) / Technology > 62 Ingeniería y operaciones afines / Engineering
Unidad administrativa:Revistas electrónicas UN > Dyna
Código ID:58979
Enviado por : Dirección Nacional de Bibliotecas STECNICO
Enviado el día :31 Oct 2017 17:20
Ultima modificación:27 Noviembre 2017 22:05
Ultima modificación:27 Noviembre 2017 22:05
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