计算机应用研究2024，Vol.41Issue(7)：1999-2004,6.DOI:10.19734/j.issn.1001-3695.2023.11.0569
基于离群点检测和自适应参数的三支DBSCAN算法
Three-ways DBSCAN algorithm based on outlier detection and adaptive parameters
摘要
Abstract
Aiming at the problems of the classical DBSCAN algorithm that it is difficult to determine the global optimal para-meters and misjudge the outliers,the algorithm firstly started from the perspective of selecting the optimal parameters,genera-ted the Eps and MinPts lists by the distribution characteristics of the data set,and then carried out the full combination opera-tion of the parameters in the two lists,and then performed the clustering of the different combinations of the parameters in or-der,so as to search for the parameter corresponding to the point of the highest accuracy rate.Finally,from the perspective of outlier,the three-branch decision-making idea was combined with the outlier detection LOF algorithm.This algorithm was compared and analysed with a variety of clustering algorithms,and the results show that this algorithm can achieve the fully au-tomated selection of the global optimal parameters as well as improve the accuracy of the clustering algorithm.关键词
DBSCAN算法/三支聚类/自适应参数/离群点检测Key words
DBSCAN algorithm/three-ways clustering/adaptive parameters/outlier detection分类
信息技术与安全科学引用本文复制引用
李志聪,孙旭阳..基于离群点检测和自适应参数的三支DBSCAN算法[J].计算机应用研究,2024,41(7):1999-2004,6.基金项目
哈尔滨师范大学双一流-提高人才培养质量资助项目(1504120015) （1504120015）
哈尔滨师范大学计算机科学与信息工程学院教育教学改革项目(JKYJGY202205) （JKYJGY202205）
