INTELLIGENT CLUSTERING TECHNIQUE BASED ON GENETIC ALGORITHM
Shaymaa Adnan Abdulrahman, Mohamed Ismail Roushdy, Abdel‐Badeeh M. Salem · International journal of intelligent computing and information sciences/International Journal of Intelligent Computing and Information Sciences · 2021
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.