A novel density peaks clustering algorithm for mixed data

doi:10.1016/j.patrec.2017.07.001

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	A novel density peaks clustering algorithm for mixed data
	Du, Mingjing 1; Ding, Shifei 1,3; Xue, Yu 2
刊名	PATTERN RECOGNITION LETTERS
	2017-10-01
卷号	97 页码:46-53
关键词	Data clustering Density peaks Entropy Mixed data
ISSN号	0167-8655
DOI	10.1016/j.patrec.2017.07.001
英文摘要	The density peaks clustering (DPC) algorithm is well known for its power on non-spherical distribution data sets. However, it works only on numerical values. This prohibits it from being used to cluster real world data containing categorical values and numerical values. Traditional clustering algorithms for mixed data use a pre-processing based on binary encoding. But such methods destruct the original structure of categorical attributes. Other solutions based on simple matching, such as K-Prototypes, need a userdefined parameter to avoid favoring either type of attribute. In order to overcome these problems, we present a novel clustering algorithm for mixed data, called DPC-MD. We improve DPC by using a new similarity criterion to deal with the three types of data: numerical, categorical, or mixed data. Compared to other methods for mixed data, DPC absolutely has more advantages to deal with non-spherical distribution data. In addition, the core of the proposed method is based on a new similarity measure for mixed data. This similarity measure is proposed to avoid feature transformation and parameter adjustment. The performance of our method is demonstrated by experiments on some real-world datasets in comparison with that of traditional clustering algorithms, such as K-Modes, K-Prototypes EKP and SBAC. (C) 2017 Elsevier B.V. All rights reserved.
资助项目	Fundamental Research Funds for the Central Universities[2017XKZD03]
WOS研究方向	Computer Science
语种	英语
出版者	ELSEVIER SCIENCE BV
WOS记录号	WOS:000411765800008
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/6804]
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Ding, Shifei
作者单位	1.China Univ Min & Technol, Sch Comp Sci & Technol, Xuzhou 221116, Peoples R China 2.Nanjing Univ Informat Sci & Technol, Sch Comp & Software, Nanjing 210044, Jiangsu, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Du, Mingjing,Ding, Shifei,Xue, Yu. A novel density peaks clustering algorithm for mixed data[J]. PATTERN RECOGNITION LETTERS,2017,97:46-53.
APA	Du, Mingjing,Ding, Shifei,&Xue, Yu.(2017).A novel density peaks clustering algorithm for mixed data.PATTERN RECOGNITION LETTERS,97,46-53.
MLA	Du, Mingjing,et al."A novel density peaks clustering algorithm for mixed data".PATTERN RECOGNITION LETTERS 97(2017):46-53.