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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