Robust K-Median and K-Means Clustering Algorithms for Incomplete Data
Joint Authors
Zhang, Yuli
Song, Shiji
Li, Jinhua
Zhou, Zhen
Source
Mathematical Problems in Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-12-04
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Incomplete data with missing feature values are prevalent in clustering problems.
Traditional clustering methods first estimate the missing values by imputation and then apply the classical clustering algorithms for complete data, such as K-median and K-means.
However, in practice, it is often hard to obtain accurate estimation of the missing values, which deteriorates the performance of clustering.
To enhance the robustness of clustering algorithms, this paper represents the missing values by interval data and introduces the concept of robust cluster objective function.
A minimax robust optimization (RO) formulation is presented to provide clustering results, which are insensitive to estimation errors.
To solve the proposed RO problem, we propose robust K-median and K-means clustering algorithms with low time and space complexity.
Comparisons and analysis of experimental results on both artificially generated and real-world incomplete data sets validate the robustness and effectiveness of the proposed algorithms.
American Psychological Association (APA)
Li, Jinhua& Song, Shiji& Zhang, Yuli& Zhou, Zhen. 2016. Robust K-Median and K-Means Clustering Algorithms for Incomplete Data. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1112183
Modern Language Association (MLA)
Li, Jinhua…[et al.]. Robust K-Median and K-Means Clustering Algorithms for Incomplete Data. Mathematical Problems in Engineering No. 2016 (2016), pp.1-8.
https://search.emarefa.net/detail/BIM-1112183
American Medical Association (AMA)
Li, Jinhua& Song, Shiji& Zhang, Yuli& Zhou, Zhen. Robust K-Median and K-Means Clustering Algorithms for Incomplete Data. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1112183
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1112183