[1]邱保志,杨洋,杜效伟..BRINK:基于局部质变因子的聚类边界检测算法[J].郑州大学学报(工学版),2012,33(03):117-120.[doi:10.3969/j.issn.1671-6833.2012.03.030]
　QIU Baozhi,YANG Yang,DU Xiaowei.BRINK: An Algorithm of Boundary Points of Clusters DetectonBased On Local Qualitative Factors[J].Journal of Zhengzhou University (Engineering Science),2012,33(03):117-120.[doi:10.3969/j.issn.1671-6833.2012.03.030]
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BRINK:基于局部质变因子的聚类边界检测算法()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
33
期数:
2012年03期
页码:
117-120
栏目:
出版日期:
2012-05-10

文章信息/Info

Title:
BRINK: An Algorithm of Boundary Points of Clusters DetectonBased On Local Qualitative Factors
作者:
邱保志; 杨洋; 杜效伟.
郑州大学 信息工程学院,河南郑州,450001, 漯河职业技术学院,河南漯河,462000
Author(s):
QIU Baozhi; YANG Yang; DU Xiaowei
1.School of lnformation Engjneering, 2hengzhou Universily , Zhengzhou 450001 ,China; 2. Luohe Yocational and Technical College.Luohe 462000,China
关键词:
边界检测;  局部质变因子;  聚类
Keywords:
boundary detection; local qualitative factor;  cluster
分类号:
TP391
DOI:
10.3969/j.issn.1671-6833.2012.03.030
摘要:
为有效检测聚类的边界,提出了一种基于局部质变因子的聚类边界检测算法(BRINK).该算法使用加权欧式距离技术解决现有聚类边界检测算法不能适用于高维数据的问题,根据局部质变因子在聚类的边界具有稍大于1的特征束识别聚类的边界.实验结果表明,该算法能有效的检测出聚类的边界.
Abstract:
In order to detect boundary points of clusters efficiently, we present an algorithm of boundary pointsdetection based on local qualitative factors ( BRINK). This algorithm uses weighted euclidean distance to solvehigh dimensional data problem which most of the existing clusters detecting algorithms can not deal with. Ae.cording to the feature of local qualitative factors ,the individual finds that it is lightly larger than 1 in boundarypoints of clusters, we can detect the boundary points with the former two processes, As shown by the experi.mental results, BRlNK can deteet boundary points in noisy high-dimensional datasets containing clusters of ar-.bitrary shapes,sizes and different densities.
更新日期/Last Update: 1900-01-01