abdulrahman, S., Roushdy, M., Salem, A. (2021). INTELLIGENT CLUSTERING TECHNIQUE BASED ON GENETIC ALGORITHM. test, 21(1), 19-32. doi: 10.21608/ijicis.2021.148607
shaymaa abdulrahman; Mohamed Ismail Roushdy; Abdel-Badeeh M. Salem. "INTELLIGENT CLUSTERING TECHNIQUE BASED ON GENETIC ALGORITHM". test, 21, 1, 2021, 19-32. doi: 10.21608/ijicis.2021.148607
abdulrahman, S., Roushdy, M., Salem, A. (2021). 'INTELLIGENT CLUSTERING TECHNIQUE BASED ON GENETIC ALGORITHM', test, 21(1), pp. 19-32. doi: 10.21608/ijicis.2021.148607
abdulrahman, S., Roushdy, M., Salem, A. INTELLIGENT CLUSTERING TECHNIQUE BASED ON GENETIC ALGORITHM. test, 2021; 21(1): 19-32. doi: 10.21608/ijicis.2021.148607

INTELLIGENT CLUSTERING TECHNIQUE BASED ON GENETIC ALGORITHM

International Journal of Intelligent Computing and Information Sciences
Article 2, Volume 21, Issue 1, February 2021, Pages 19-32    PDF (744.65 K)
Document Type: Original Article
DOI: 10.21608/ijicis.2021.148607
Authors
shaymaa abdulrahman* 1; Mohamed Ismail Roushdy2; Abdel-Badeeh M. Salem3
1ain shams university
2Faculty of Computer and Information Technology, Future University in Egypt, Cairo, Egypt
3Computer 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.
Keywords
data mining; clustering; genetic algorithms; feature extraction; K-means
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