INTELLIGENT CLUSTERING TECHNIQUE BASED ON GENETIC ALGORITHM | ||||
| International Journal of Intelligent Computing and Information Sciences | ||||
| Article 2, Volume 21, Issue 1, February 2021, Page 19-32 PDF (744.65 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/ijicis.2021.148607 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
shaymaa abdulrahman  1; Mohamed Ismail Roushdy 2; Abdel-Badeeh M. Salem 3
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| 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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