Fuzzy C-Means Clustering Using Asymmetric Loss Function

Fuzzy C-Means Clustering Using Asymmetric Loss Function

In this work, a fuzzy clustering algorithm is proposed based on the asymmetric loss function instead of the usual symmetric dissimilarities. Linear Exponential (LINEX) loss function is a commonly used asymmetric loss function, which is considered in this paper. We prove that the negative likelihood...

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Main Authors: Israa Abdzaid Atiyah, Adel Mohammadpour, Narges Ahmadzadehgol, S. Mahmoud Taheri
Format: Article
Language:English
Published: Atlantis Press 2020-03-01
Series:Journal of Statistical Theory and Applications (JSTA)
Subjects:
Fuzzy C-Means clustering
LINEX loss function
Online Access:https://www.atlantis-press.com/article/125935600/view
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spelling doaj-d1e960540f244a9395efb4239d03d4122020-11-25T03:10:02ZengAtlantis PressJournal of Statistical Theory and Applications (JSTA)2214-17662020-03-0119110.2991/jsta.d.200302.002Fuzzy C-Means Clustering Using Asymmetric Loss FunctionIsraa Abdzaid AtiyahAdel MohammadpourNarges AhmadzadehgolS. Mahmoud TaheriIn this work, a fuzzy clustering algorithm is proposed based on the asymmetric loss function instead of the usual symmetric dissimilarities. Linear Exponential (LINEX) loss function is a commonly used asymmetric loss function, which is considered in this paper. We prove that the negative likelihood of an extreme value distribution is equal to LINEX loss function and clarify some of its advantages. Using such a loss function, the so-called LINEX Fuzzy C-Means algorithm is introduced. The introduced clustering method is compared with its crisp version and Fuzzy C-Means algorithms through a few real datasets as well as some simulated datasets.https://www.atlantis-press.com/article/125935600/viewFuzzy C-Means clusteringLINEX loss function
collection DOAJ
language English
format Article
sources DOAJ
author Israa Abdzaid Atiyah
Adel Mohammadpour
Narges Ahmadzadehgol
S. Mahmoud Taheri
spellingShingle Israa Abdzaid Atiyah
Adel Mohammadpour
Narges Ahmadzadehgol
S. Mahmoud Taheri
Fuzzy C-Means Clustering Using Asymmetric Loss Function
Journal of Statistical Theory and Applications (JSTA)
Fuzzy C-Means clustering
LINEX loss function
author_facet Israa Abdzaid Atiyah
Adel Mohammadpour
Narges Ahmadzadehgol
S. Mahmoud Taheri
author_sort Israa Abdzaid Atiyah
title Fuzzy C-Means Clustering Using Asymmetric Loss Function
title_short Fuzzy C-Means Clustering Using Asymmetric Loss Function
title_full Fuzzy C-Means Clustering Using Asymmetric Loss Function
title_fullStr Fuzzy C-Means Clustering Using Asymmetric Loss Function
title_full_unstemmed Fuzzy C-Means Clustering Using Asymmetric Loss Function
title_sort fuzzy c-means clustering using asymmetric loss function
publisher Atlantis Press
series Journal of Statistical Theory and Applications (JSTA)
issn 2214-1766
publishDate 2020-03-01
description In this work, a fuzzy clustering algorithm is proposed based on the asymmetric loss function instead of the usual symmetric dissimilarities. Linear Exponential (LINEX) loss function is a commonly used asymmetric loss function, which is considered in this paper. We prove that the negative likelihood of an extreme value distribution is equal to LINEX loss function and clarify some of its advantages. Using such a loss function, the so-called LINEX Fuzzy C-Means algorithm is introduced. The introduced clustering method is compared with its crisp version and Fuzzy C-Means algorithms through a few real datasets as well as some simulated datasets.
topic Fuzzy C-Means clustering
LINEX loss function
url https://www.atlantis-press.com/article/125935600/view
work_keys_str_mv AT israaabdzaidatiyah fuzzycmeansclusteringusingasymmetriclossfunction
AT adelmohammadpour fuzzycmeansclusteringusingasymmetriclossfunction
AT nargesahmadzadehgol fuzzycmeansclusteringusingasymmetriclossfunction
AT smahmoudtaheri fuzzycmeansclusteringusingasymmetriclossfunction
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