Semi-supervised possibilistic c-means clustering algorithm based on feature weights for imbalanced data-Reference-Cited by-同舟云学术

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Semi-supervised possibilistic c-means clustering algorithm based on feature weights for imbalanced data

Published:2024-02 Issue: Volume:286 Page:111388
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Yu Haiyan,Xu Xiaoyu^ORCID,Li Honglei^ORCID,Wu Yuting,Lei Bo

Publisher

Elsevier BV

Reference70 articles.

1. FCM: the fuzzy c-means clustering algorithm;Bezdek;Comput. Geosci.,1984

2. A possibilistic approach to clustering;Krishnapuram;IEEE Trans. Fuzzy Syst.,1993

3. Generalized Possibilistic Fuzzy C-Means with novel cluster validity indices for clustering noisy data;Askari;Appl. Soft Comput.,2017

4. Integrating rough set principles in the graded possibilistic clustering;Ferone;Inf. Sci. (Ny),2019

5. Global intuitionistic fuzzy weighted C-ordered means clustering algorithm;Kaushal;Inf. Sci. (Ny),2023

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1. Revisiting Possibilistic Fuzzy C-Means Clustering Using the Majorization-Minimization Method;Entropy;2024-08-06

2. Knowledge-based system and expectation-maximization to discovering causes of imperfect labels in vehicular networks clustering;Knowledge-Based Systems;2024-07

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