计算机工程与应用2017，Vol.53Issue(21)：1-7,7.DOI:10.3778/j.issn.1002-8331.1707-0202
K最近邻算法理论与应用综述
Survey on theory and application of k-Nearest-Neighbors algorithm
摘要
Abstract
K nearest neighbor(kNN)algorithm is a simple classification algorithm, the algorithm consists of two steps:(1)Find out a set of k on a given search training set measure at a distance.(2)The classification is according to the most consistent classes in this kNN algorithm. The non-parametric property of kNN algorithm makes it very easy to implement, and its classification error is restricted by two times of the Bayes error. Therefore, the kNN algorithm is still the most popular choice for pattern classification. This paper summarizes many literatures by using kNN algorithm, expounding the im-provement methods used in each document, and analyzing the experimental results. By analyzing the kNN algorithm in face recognition, text recognition, medical image-processing and other applications achieved good classification results, this paper is very promising for the development of kNN algorithm.关键词
k最近邻算法(kNN)/人脸识别/文字识别/医学图像处理Key words
k-Nearest-Neighbors(kNN)algorithm/face recognition/text recognition/medical image processing分类
信息技术与安全科学引用本文复制引用
毋雪雁,王水花,张煜东..K最近邻算法理论与应用综述[J].计算机工程与应用,2017,53(21):1-7,7.基金项目
国家自然科学基金(No.61602250,No.61503188) （No.61602250,No.61503188）
江苏省自然科学基金(No.BK20150983,No.BK20150982) （No.BK20150983,No.BK20150982）
江苏省高校自然科学研究面上项目(No.16KJB520025,No.15KJB470010). （No.16KJB520025,No.15KJB470010）
