INTELLIGENT CLUSTERING TECHNIQUE BASED ON GENETIC ALGORITHM

Document Type : Original Article

Authors

1 ain shams university

2 Faculty of Computer and Information Technology, Future University in Egypt, Cairo, Egypt

3 Computer Sciece Department, Faculty of Computer and Information Sciences, Ain Shams University

Abstract

This paper focuses on the problems of data clustering where the similarity between different objects is estimated with the use of the Euclidean distance metric. Also, K-Means is used to remove data noise, genetic algorithms are used for finding the optimal set of features and the Support Vector, Machine (SVM) is used as a classifier. The experimental results prove that the proposed model has attained an accuracy of 94.79 % when using three datasets taken from the UCI repository.

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