Initial Seeds Selection in Dynamic Clustering Method Based on Data Depth

被引：0

作者：

Zhang, Caiya ^{[1
]}

Jin, Ze ^{[2
]}

机构：

[1] Zhejiang Univ City Coll, Sch Comp & Comp Sci, Hangzhou 310003, Zhejiang, Peoples R China

[2] Cornell Univ, Dept Stat Sci, Ithaca, NY USA

来源：

INTELLIGENCE SCIENCE AND BIG DATA ENGINEERING: BIG DATA AND MACHINE LEARNING TECHNIQUES, ISCIDE 2015, PT II | 2015年 / 9243卷

关键词：

Clustering; Initial seeds; Projection depth; CONSTITUTION; ATOMS;

D O I：

10.1007/978-3-319-23862-3_60

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Resorting to the theory of atomic models and the tool of data depth, we propose a novel method for initial seeds selection in dynamic clustering method. We define the cohesion of a point in a given data set, which includes the information of the significance and locations of neighboring points together. Then, the dynamic clustering algorithm based on cohesion is proposed. Compared with the density-based dynamic clustering algorithm, the clustering results demonstrate that our proposed method is more effective and robust.

引用

页码：603 / 611

页数：9

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