A new edited k-nearest neighbor rule in the pattern classification problem

摘要

A new edited k-nearest neighbor (k–NN) rule is proposed. For every sample y in the edited reference set, all the k- or (k+l)-nearest neighbors of y must be in the class to which y belongs. Here l denotes the number of samples which tie with the kth nearest neighbor of y with respect to the distance from y. The performance of the rule proposed has been investigated using three classification examples. As a result, it is shown that the rule proposed will yield good results in many pattern classification problems.