基于数据场的改进DBSCAN聚类算法OACSCDCSTPCD
An Improved DBSCAN Clustering Algorithm Based on Data Field
DBSCAN(density based spatial clustering of applications with noise)算法是一种典型的基于密度的聚类算法.该算法可以识别任意形状的类簇,但聚类结果依赖于参数Eps和MinPts的选择,而且对于一些密度差别较大的数据集,可能得不到具有正确类簇个数的聚类结果,也可能将部分数据错分为噪声.为此,利用数据场能较好描述数据分布,反映数据关系的优势,提出了一种基于数据场的改进DBSCAN聚类算法…查看全部>>
DBSCAN (density based spatial clustering of applications with noise) algorithm is a typical density-based clustering algorithm. The algorithm can discover the arbitrary-shaped clusters. However, the clustering results depend on the two parameters Eps and MinPts which are chosen by users. And for some datasets with large density differences, either the clustering results may have the incorrect cluster number, or the algorithm may label part of the data as noi…查看全部>>
杨静;高嘉伟;梁吉业;刘杨磊
山西大学计算智能与中文信息处理教育部重点实验室,太原030006山西大学计算机与信息技术学院,太原030006山西大学计算智能与中文信息处理教育部重点实验室,太原030006山西大学计算机与信息技术学院,太原030006
信息技术与安全科学
DBSCAN算法数据场聚类
DBSCAN algorithm data field clustering
《计算机科学与探索》 2012 (10)
903-911,9
The Special Prophase Project on the National Grand Basic Research 973 Program of China under Grant No.2011CB311805(国家重点基础研究发展规划(973)前期研究专项)the Key Problems in Science and Technology Project of Shanxi Province under Grant No.20110321027-01(山西省科技攻关计划项目)the Construction Project of the Science and Technology Basic Condition Platform of Shanxi Province under Grant No.2012091002-0101(山西省科技基础条件平台建设项目).
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