Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Comparative Efficiency Analysis of K-Means, Fuzzy Class and Rough Class Clustering Algorithm with IRIS Dataset with Multiple Centroid

Author : Arup Kumar Bhattacharjee 1 Arup Kumar Bhattacharjee 2 Soumen Mukherjee 3 Krishnendu Paul 4 Dipan Mitra 5 Poulami Mukherjee 6

Date of Publication :7th October 2016

Abstract: Data analysis is considered as an efficient and handy tool for processing huge amount of data which is very tough and data mining technology identifies patterns and trends of these data. This technique is used to extract the unknown pattern from a large dataset helping unreal time applications. Raw data from this dataset are classified by using cluster analysis-an important method for classifying data, finding clusters based on similarities with the same cluster and dissimilarities with others. There are various algorithms which are used to solve this problem like, K-Means, Fuzzy C Means (FCM), Rough C means, Rough Fuzzy C means. A comparative study of these algorithms is done in this paper. These algorithms are implemented in MATLAB using a set of real life data sets. So, this paper is a blend of Mathematics, Statistics and Computer Application.

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