Adaptive Nearest Neighbors for Classification Jhun, Myoung-Shic; Choi, In-Kyung;
The -Nearest Neighbors Classification(KNNC) is a popular non-parametric classification method which assigns a fixed number of neighbors to every observation without consideration of the local feature of the each observation. In this paper, we propose an Adaptive Nearest Neighbors Classification(ANNC) as an alternative to KNNC. The proposed ANNC method adapts the number of neighbors according to the local feature of the observation such as density of data. To verify characteristics of ANNC, we compare the number of misclassified observation with KNNC by Monte Carlo study and confirm the potential performance of ANNC method.