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

Iris Data Classification Using Fuzzy Clustering With Varying Parameters

Author : Nisha Singh ¹

Date of Publication :13th July 2017

Abstract: In the field of various real environment, there is problem of clubbing the data according to their behavior or working techniques. Fuzzy clustering can be used where any data belongs to more than one class or bucket formed anywhere. That means the decision to keep them in any bucket is done by applying some similarity measurements. According to this the data points of any data set can belong to more than one class, even having different membership function value to different class. Fuzzy clustering is comprising two very dissimilar data types as fuzzy data and usual (crisp) data. It is a kind of function working on probabilistic mode of evaluating the values. Where the whole process is done without training of values to that system is done. In this paper the data used is iris flower data based problems are used to be clustered with the proper usage of fuzzy clustering model.

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