Iwashita, Adriana S. [UNESP]Papa, Joao P. [UNESP]Falcao, Alexandre X.Lotufo, Roberto A.Araujo Oliveira, Victor M. deCosta de Albuquerque, Victor H.Tavares, Joao Manuel R. S.IEEE2020-12-102020-12-102012-01-012012 21st International Conference On Pattern Recognition (icpr 2012). New York: Ieee, p. 1233-1236, 2012.1051-4651http://hdl.handle.net/11449/196064In this paper we present an optimization of the Optimum-Path Forest classifier training procedure, which is based on a theoretical relationship between minimum spanning forest and optimum-path forest for a specific path-cost function. Experiments on public datasets have shown that the proposed approach can obtain similar accuracy to the traditional one hut with faster data training.1233-1236engTrabalho apresentado em eventoWOS:000343660601081