Clustering Mixed Data by Fast Search and Find of Density Peaks. (5th July 2017)

• Record Type: Journal Article
• Authors: Liu, Shihua; Zhou, Bingzhong; Huang, Decai; Shen, Liangzhong
• Other Names: Gil-Lafuente Anna M. Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2017(2017)
• Publication Date: 2017-07-05
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2017/5060842
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : Aiming at the mixed data composed of numerical and categorical attributes, a new unified dissimilarity metric is proposed, and based on that a new clustering algorithm is also proposed. The experiment result shows that this new method of clustering mixed data by fast search and find of density peaks is feasible and effective on the UCI datasets.