Rough Set Theory (RST) is a technique for data analysis. In this study, we use RST to improve the performance of k-NN method. The RST is used to edit and reduce 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 k-NN method using these techniques.Applications in Artificial Intelligence - Learning and Neural NetsRed de Universidades con Carreras en Informática (RedUNCI
