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**Submission of manuscripts for Volume 08, Issue 05 (September, 2019) is open.

 

COMPARATIVE DATA ANALYSIS BASED ON FUZZY CLUSTERING ALGORITHM AND FGA


Author : Omlata Dohare, Prof. Aishwarya Vishwakarma
[ Volume No.:VII, Issue No.V-SEP 2018] [Page No : 889-893] [2018]

The fundamental knowledge clustering drawback may be defined as searching for groups in data or grouping connected objects together. Many alternative clustering techniques are proposed over the years like Partitioning strategies, Density-based strategies and Grid-based methods. During this analysis work vital clustering algorithms particularly representative object based mostly FCM (Fuzzy C-Means) clustering algorithms are compared our proposed algorithms. The quality analysis of the prediction provided by the proposed algorithm was measured by means of statistical tests. These algorithms are applied and performance is evaluated on the idea of the efficiency of clustering output. During this analysis the information bunch algorithms supported fuzzy techniques. These fuzzy bunch algorithms are wide studied and applied in a type of substantive areas. Our proposed Fuzzy clustering with genetic algorithmic program (FGA). These fuzzy bunch algorithms are wide studied and applied in a type of substantive areas. Our proposed Fuzzy clustering with genetic algorithmic program (FCGA)

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