Kernel-based K-Nearest Neighbor Classification
Yanli Zhou, Chuangming Zhou, Pla Xi · Aeronautical Computing Technique · 2006
In order to overcome the disadvantages of traditional K-NN classification algorithm,this paper proposes a K-nearest neighbor classification algorithm based on kernel.The idea of the algorithm is firstly to map the data from their original space to a high dimensional space(or kernel space) where the data are expected to be more separable,then to perform K-NN classification in the high dimensional space.The performance of new algorithm is demonstrated to be superior to that of K-NN classification algorithm by experiments on artificial and real data.