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Revista de Matemática Teoría y Aplicaciones
versión impresa ISSN 1409-2433
Resumen
FLORES-CRUZ, Jorge et al. A classifier system using smooth graph coloring. Rev. Mat [online]. 2017, vol.24, n.1, pp.129-156. ISSN 1409-2433. http://dx.doi.org/10.15517/rmta.v24i1.27795.
Unsupervised classifiers allow clustering methods with less or no human intervention. Therefore it is desirable to group the set of items with less data processing. This paper proposes an unsupervised classifier system using the model of soft graph coloring. This method was tested with some classic instances in the literature and the results obtained were compared with classifications made with human intervention, yielding as good or better results than supervised classifiers, sometimes providing alternative classifications that considers additional information that humans did not considered.
Palabras clave : soft coloring; unsupervised classification; clustering; optimization.