计算机与数字工程2019，Vol.47Issue(5)：1175-1178,4.DOI:10.3969/j.issn.1672-9722.2019.05.031
基于网格山脊点的异常点检测
An Outlier Detection Based on Grid Ridge
戴楠 1严悍 1卓勤政 1马玲玲1
作者信息
- 1. 南京理工大学计算机科学与技术学院 南京 210094
- 折叠
摘要
Abstract
The LOF(Local Outlier Factor)algorithm is one of the most practical and effective detection methods. However, the algorithm often takes a lot of time and space when dealing with large-scale data sets. At present,the grid-based outlier detection algorithm reduces the time and space consumption of the algorithm,but the time and space consumption is still relatively large. In this paper,an outlier detection algorithm based on grid ridge is proposed. The algorithm is divided into spatial grid cells according to the data distribution,and then the height of each grid ridge is calculated,and the area with low grid ridge is selected. Finally,the LOF algorithm is detected in the low ridge area. The experimental results show that the efficiency of the algorithm is significantly im?proved compared with the current grid-based outlier detection algorithm.关键词
山脊点/LOF/网格Key words
ridge point/LOF/grid分类
信息技术与安全科学引用本文复制引用
戴楠,严悍,卓勤政,马玲玲..基于网格山脊点的异常点检测[J].计算机与数字工程,2019,47(5):1175-1178,4.
