New prototype selection rule integrated condensing with editing process for the nearest neighbor rules

A new prototype selection method was proposed to reduce the training set for the nearest neighbor rule. The method aimed to integrate the advantage of editing and condensing method, and it only selects the points in class boundary into prototype set. It used information contained in internal points to `clean´ or edit overlapping and noise of training set, then condensing process which only keeps border points was used to obtain prototype set. Computational results show that it can obtain satisfactory performance and higher condensing rate than popular instance reduction algorithm