A Robust k-Means Clustering Algorithm Based on Observation Point Mechanism
Joint Authors
Huang, Joshua Zhexue
He, Yulin
Zhang, Xiaoliang
Jin, Yi
Qin, Honglian
Azhar, Muhammad
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-03-30
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
The k-means algorithm is sensitive to the outliers.
In this paper, we propose a robust two-stage k-means clustering algorithm based on the observation point mechanism, which can accurately discover the cluster centers without the disturbance of outliers.
In the first stage, a small subset of the original data set is selected based on a set of nondegenerate observation points.
The subset is a good representation of the original data set because it only contains all those points that have a higher density of the original data set and does not include the outliers.
In the second stage, we use the k-means clustering algorithm to cluster the selected subset and find the proper cluster centers as the true cluster centers of the original data set.
Based on these cluster centers, the rest data points of the original data set are assigned to the clusters whose centers are the closest to the data points.
The theoretical analysis and experimental results show that the proposed clustering algorithm has the lower computational complexity and better robustness in comparison with k-means clustering algorithm, thus demonstrating the feasibility and effectiveness of our proposed clustering algorithm.
American Psychological Association (APA)
Zhang, Xiaoliang& He, Yulin& Jin, Yi& Qin, Honglian& Azhar, Muhammad& Huang, Joshua Zhexue. 2020. A Robust k-Means Clustering Algorithm Based on Observation Point Mechanism. Complexity،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1141564
Modern Language Association (MLA)
Zhang, Xiaoliang…[et al.]. A Robust k-Means Clustering Algorithm Based on Observation Point Mechanism. Complexity No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1141564
American Medical Association (AMA)
Zhang, Xiaoliang& He, Yulin& Jin, Yi& Qin, Honglian& Azhar, Muhammad& Huang, Joshua Zhexue. A Robust k-Means Clustering Algorithm Based on Observation Point Mechanism. Complexity. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1141564
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1141564