一个高效的KNN分类算法

计算机科学 ›› 2008, Vol. 35 ›› Issue (3): 170-172.

一个高效的KNN分类算法

张著英黄玉龙王翰虎

贵州大学计算机科学技术学院,贵州贵阳550025

出版日期:2018-11-16 发布日期:2018-11-16

ZHANG Zhu-Ying, HUANG Yu-Long ,WANG Han-Hu （College of Computer Science Technology,Guizhou University,Guiyang 550025）

Online:2018-11-16 Published:2018-11-16

摘要/Abstract

摘要： KNN算法是数据挖掘技术中比较常用的分类算法，由于其实现的简单性，在很多领域得到了广泛的应用。但是，当样本容量较大以及特征属性较多时，KNN算法分类的效率就将大大降低。本文将粗糙集理论应用到KNN算法中，实现属性约简，提出了一种新的KNN分类方法，解决了KNN算法分类效率低的缺点，从而可使KNN算法能够得到更广泛的应用。

关键词: 数据挖掘 KNN分类粗糙集属性约简

Abstract: KNN algorithm has been widely used in many data mining areas due to its simplicity. When the samples become more and more large and characteristic attributes become more and more numerous, KNN algorithm becomes much lower. A new KNN algorithm based rough

Key words: Data mining, KNN classification,Rough set, Attributes induction

张著英黄玉龙王翰虎. 一个高效的KNN分类算法[J]. 计算机科学, 2008, 35(3): 170-172. https://doi.org/

ZHANG Zhu-Ying, HUANG Yu-Long ,WANG Han-Hu （College of Computer Science Technology,Guizhou University,Guiyang 550025）. [J]. Computer Science, 2008, 35(3): 170-172. https://doi.org/

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