A method to edit training set based on rough sets.(Report) From: International Journal of Computational IntelligenceResearch | Date: July 1, 2007| Author: Caballero, Yaile; Bello, Rafael; Salgado, Yanitza; Garcia, Maria M. | COPYRIGHT 2007 Research India Publications. This material is published under license from the publisher through the Gale Group, Farmington Hills, Michigan.  All inquiries regarding rights should be directed to the Gale Group.Copyright information

Abstract: Rough Set Theory (RST) is a technique for data analysis. In this paper, we use RST to improve the performance of the k-NN method and the MLP neural network. The RST is used to edit the training set. We propose two methods to edit training sets, which are based on the lower and upper approximations. Experimental results show a satisfactory performance of the k-NN method and MLP using these techniques.

Keywords: k-NN method, MLP, Rough Set Theory, data analysis, e...

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