MODIFIED POSSIBILISTIC FUZZY C-MEANS ALGORITHM FOR CLUSTERING INCOMPLETE DATA SETS

MODIFIED POSSIBILISTIC FUZZY C-MEANS ALGORITHM FOR CLUSTERING INCOMPLETE DATA SETS

A possibilistic fuzzy c-means (PFCM) algorithm is a reliable algorithm proposed to deal with the weaknesses associated with handling noise sensitivity and coincidence clusters in fuzzy c-means (FCM) and possibilistic c-means (PCM). However, the PFCM algorithm is only applicable to complete data sets...

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Bibliographic Details
Main Authors: Rustam, Koredianto Usman, Mudyawati Kamaruddin, Dina Chamidah, Nopendri, Khaerudin Saleh, Yulinda Eliskar, Ismail Marzuki
Format: Article
Language:English
Published: CTU Central Library 2021-04-01
Series:Acta Polytechnica
Subjects:
incomplete data
fuzzy clustering
possibilistic clustering
missing values imputation.
Online Access:https://ojs.cvut.cz/ojs/index.php/ap/article/view/6763

Internet

https://ojs.cvut.cz/ojs/index.php/ap/article/view/6763

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