青岛大学学报（自然科学版）2017，Vol.30Issue(1)：85-90,6.DOI:10.3969/j.issn.1006-1037.2017.02.17
基于超球区域划分的改进KNN算法
An Improved KNN Algorithm Based on Hyper-sphere Region Partition
郝卫杰 1王艳飞 1胡敬伟 1张公敬1
作者信息
- 1. 青岛大学计算机科学技术学院,青岛 266071
- 折叠
摘要
Abstract
Referring to the calculation of samples' similarity is complex, the redundancy of KNN algorithm is high and its efficiency is low, for this problem, the article proposed improved KNN algorithm based on hyper-sphere region partition is one method modifying from classical KNN algorithm.By constructing same radius hyper-spheres, all training samples are assigned to the appropriate hyper spheres separately, so the type of a test sample can be determined by the new training sample set formed by samples included by its k nearest hyper-spheres.To ensure calculation efficiency, one algorithm is designed to find the right radius to control the amount of hyper-spheres.Experimental results show that the improved algorithm gets higher efficiency and performance than the traditional KNN algorithm.关键词
KNN算法/区域划分/超球Key words
KNN algorithm/region partition/hyper-sphere分类
信息技术与安全科学引用本文复制引用
郝卫杰,王艳飞,胡敬伟,张公敬..基于超球区域划分的改进KNN算法[J].青岛大学学报（自然科学版）,2017,30(1):85-90,6.
