Fuzzy C-Means and Fuzzy K-Means Algorithms using Fuzzy Functional Dependencies

Fuzzy C-Means (FCM) is c- clustering algorithms for fuzzy dataset of n objects. Fuzzy K-Means (FKM) is k-clustering algorithms of c-clusters. In this paper, we proposed fuzzy c-means clustering algorithm using fuzzy association functional dependencies and Fuzzy K-means MapReduce algorithms using fuz...

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Bibliographic Details
Published in:International Conference on Fuzzy Theory and Its Applications (Print) pp. 1 - 5
Main Author: Reddy Poli, Venkata Subba
Format: Conference Proceeding
Language:English
Published: IEEE 03.11.2022
Subjects:
Business intelligence
Clustering algorithms
Pain
ISSN:2377-5831
Online Access:Get full text
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Summary:Fuzzy C-Means (FCM) is c- clustering algorithms for fuzzy dataset of n objects. Fuzzy K-Means (FKM) is k-clustering algorithms of c-clusters. In this paper, we proposed fuzzy c-means clustering algorithm using fuzzy association functional dependencies and Fuzzy K-means MapReduce algorithms using fuzzy association multivalued functional dependencies. We studied fuzzy c-means and fuzzy k-means algorithms in different way. Fuzzy functional dependencies applied on fuzzy c-means clustering and fuzzy k-means clustering. These fuzzy MapReduce algorithms useful quick arrive solutiosn for Clustering. Some examples are given for FCM and FKM.
ISSN:2377-5831
DOI:10.1109/iFUZZY55320.2022.9985227