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http://dx.doi.org/10.5351/KJAS.2010.23.6.1093

On the Use of Modified Adaptive Nearest Neighbors for Classification  

Maeng, Jin-Woo (Department of Statistics, Korea University)
Bang, Sung-Wan (Department of Statistics, Korea University)
Jhun, Myoung-Shic (Department of Statistics, Korea University)
Publication Information
The Korean Journal of Applied Statistics / v.23, no.6, 2010 , pp. 1093-1102 More about this Journal
Abstract
Even though the k-Nearest Neighbors Classification(KNNC) is one of the popular non-parametric classification methods, it does not consider the local features and class information for each observation. In order to overcome such limitations, several methods have been developed such as Adaptive Nearest Neighbors Classification(ANNC) and Modified k-Nearest Neighbors Classification(MKNNC). In this paper, we propose the Modified Adaptive Nearest Neighbors Classification(MANNC) that employs the advantages of both the ANNC and MKNNC. Through a real data analysis and a simulation study, we show that the proposed MANNC outperforms other methods in terms of classification accuracy.
Keywords
Adaptive nearest neighbors; classification analysis; k-nearest neighbors; modified adaptive nearest neighbors;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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