Journal of Statistical Theory and Applications

Volume 18, Issue 2, June 2019, Pages 147 - 154

The LINEX Weighted k-Means Clustering

Authors
Narges Ahmadzadehgoli1, Adel Mohammadpour2, *, Mohammad Hassan Behzadi1
1 Department of Statistics, Science and Research Branch, Islamic Azad University, Tehran, Iran
2 Department of Statistics, Faculty of Mathematics & Computer Science, Amirkabir University of Technology (Tehran Polytechnic), 424 Hafez Avenue, Tehran, Iran
*Corresponding author. Email: adel@aut.ac.ir
Corresponding Author
Adel Mohammadpour
Received 24 August 2017, Accepted 30 June 2018, Available Online 30 May 2019.
DOI
https://doi.org/10.2991/jsta.d.190524.001How to use a DOI?
Keywords
LINEX loss function, Feature weights, Weighted k-means, Clustering
Abstract

LINEX weighted k-means is a version of weighted k-means clustering, which computes the weights of features in each cluster automatically. Determining which entity is belonged to which cluster depends on the cluster centers. In this study, the asymmetric LINEX loss function is used to compute the dissimilarity in the weighted k-means clustering. So, the cluster centroids are obtained by minimizing a LINEX based cost function. This loss function is used as a dissimilarity measure in clustering when one wants to overestimate or underestimate the cluster centroids, which helps to reduce some errors of misclassifying entities. Therefore, we discuss the LINEX weighted k-means algorithm. We examine the accuracy of the algorithm with some synthetic and real datasets.

Copyright
© 2019 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
Journal of Statistical Theory and Applications
Volume-Issue
18 - 2
Pages
147 - 154
Publication Date
2019/05
ISSN (Online)
2214-1766
ISSN (Print)
1538-7887
DOI
https://doi.org/10.2991/jsta.d.190524.001How to use a DOI?
Copyright
© 2019 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Narges Ahmadzadehgoli
AU  - Adel Mohammadpour
AU  - Mohammad Hassan Behzadi
PY  - 2019
DA  - 2019/05
TI  - The LINEX Weighted k-Means Clustering
JO  - Journal of Statistical Theory and Applications
SP  - 147
EP  - 154
VL  - 18
IS  - 2
SN  - 2214-1766
UR  - https://doi.org/10.2991/jsta.d.190524.001
DO  - https://doi.org/10.2991/jsta.d.190524.001
ID  - Ahmadzadehgoli2019
ER  -