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DYNA

versão impressa ISSN 0012-7353

Resumo

FERNANDEZ-HERNANDEZ, Yumilka B. et al. An improvement to the classification based on the measurement of the similarity quality using fuzzy relations. Dyna rev.fac.nac.minas [online]. 2015, vol.82, n.193, pp.70-76. ISSN 0012-7353.  http://dx.doi.org/10.15446/dyna.v82n193.45989.

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.

Palavras-chave : classification rules; fuzzy sets; similarity relations.

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