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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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 |
_version_ |
1724661119347326976 |