Using rough sets to edit training set in k-NN method
Y. CabaIlero, Rafael Bello, María Matilde García, Yaimara Pizano, Sonia Joseph, Yudenia Cristina Galbán Lezcano · 2005
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. 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 using these techniques.