计算机科学与探索2011，Vol.5Issue(5)：467-473,7.DOI:10.3778/j.issn.1673-9418.2011.05.009
最近邻分类方法的研究
Research on Nearest Neighbors Classification Techniques
摘要
Abstract
This paper studies classification techniques based on nearest-neighbor (NN), and designs a classification algorithm based on the shelly-NN (SNN) approach, which is without bias at selecting nearest neighbors. Traditional kNN classification and the SNN model are studied at the ideas of algorithm design and key techniques. Then they are also compared at the classification accuracy using several UCI data sets. Based on these researches, the paper gives the environment conditions suitable for the algorithms and analyzes the possible reasons. The results demonstrate that SNN algorithm is not sensitive to distance metrics and performs better at the classification accuracy on large data sets.关键词
分类/k近邻算法/S近邻算法/分类准确率Key words
classification/ k nearest neighbor algorithm/ shelly nearest neighbor algorithm/ classification accuracy分类
信息技术与安全科学引用本文复制引用
钟智,朱曼龙,张晨,黄樑昌..最近邻分类方法的研究[J].计算机科学与探索,2011,5(5):467-473,7.基金项目
The National Natural Science Foundation of China under Grant No.90718020(国家自然科学基金) （国家自然科学基金）
the National Grand Basic Research 973 Program of China under Grant No.2008CB317108(国家重点基础研究发展规划(973)) （国家重点基础研究发展规划(973）
the Science Research Foundation of Education Department of Guangxi,China under Grant No.200911LX27(广西教育厅科研基金项目) （广西教育厅科研基金项目）
the Innovation Project of Guangxi Graduate Education under Grant No.2009106020812M63(广西研究生教育创新计划项目) （广西研究生教育创新计划项目）
the Australian Research Council under Grant No.DP0985456(澳大利亚ARC基金). （澳大利亚ARC基金）
