JOURNAL ARTICLE

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

Abstract

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.

Keywords:
Fuzzy clustering Fuzzy classification Fuzzy logic Fuzzy set operations Defuzzification Data mining Fuzzy number Neuro-fuzzy Computer science Cluster analysis FLAME clustering Algorithm Fuzzy associative matrix Artificial intelligence Fuzzy set Mathematics Pattern recognition (psychology) Fuzzy control system Canopy clustering algorithm

Metrics

4
Cited By
0.78
FWCI (Field Weighted Citation Impact)
13
Refs
0.72
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Clustering Algorithms Research
Physical Sciences →  Computer Science →  Artificial Intelligence
Data Management and Algorithms
Physical Sciences →  Computer Science →  Signal Processing
Data Mining Algorithms and Applications
Physical Sciences →  Computer Science →  Information Systems

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