A k-Deviation Density Based Clustering Algorithm
Joint Authors
Jinyin, Chen
Jungan, Chen
Dongyong, Yang
Jun, Li
Source
Mathematical Problems in Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-02-26
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
Due to the adoption of global parameters, DBSCAN fails to identify clusters with different and varied densities.
To solve the problem, this paper extends DBSCAN by exploiting a new density definition and proposes a novel algorithm called k-deviation density based DBSCAN (kDDBSCAN).
Various datasets containing clusters with arbitrary shapes and different or varied densities are used to demonstrate the performance and investigate the feasibility and practicality of kDDBSCAN.
The results show that kDDBSCAN performs better than DBSCAN.
American Psychological Association (APA)
Jungan, Chen& Jinyin, Chen& Dongyong, Yang& Jun, Li. 2018. A k-Deviation Density Based Clustering Algorithm. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-16.
https://search.emarefa.net/detail/BIM-1207084
Modern Language Association (MLA)
Jungan, Chen…[et al.]. A k-Deviation Density Based Clustering Algorithm. Mathematical Problems in Engineering No. 2018 (2018), pp.1-16.
https://search.emarefa.net/detail/BIM-1207084
American Medical Association (AMA)
Jungan, Chen& Jinyin, Chen& Dongyong, Yang& Jun, Li. A k-Deviation Density Based Clustering Algorithm. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-16.
https://search.emarefa.net/detail/BIM-1207084
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1207084
