Fuzzy Rough Positive Region Based Nearest Neighbour Classification

We propose a classifier that uses fuzzy rough set theory to improve the Fuzzy Nearest Neighbour (FNN) classifier. We show that previous attempts to use fuzzy rough set theory to improve the FNN algorithm have some shortcomings and we overcome them by using the fuzzy positive region to measure the quality of the nearest neighbours in the FNN classifier. A preliminary experimental evaluation shows that the new approach generally improves upon existing methods.