PCA-Based Model to Enhance The Performance of Data‎Clustering Using A Metaheuristic Algorithm

  • Authors

    • Shailendra Singh Yadav Department of Computer Science & Engineering, Parul Institute of Engineering & Technology, Faculty of Engineering and Technology, Parul University,Waghodia Vadodara, India
    • Kamal Sutaria Department of Computer Science & Engineering, Parul Institute of Engineering & Technology, Faculty of Engineering and Technology, Parul University,Waghodia Vadodara, India
    https://doi.org/10.14419/gcjafw37

    Received date: July 15, 2025

    Accepted date: August 25, 2025

    Published date: September 9, 2025

  • Clustering; Preprocessing; Enhanced Grey Wolf Optimizer; PCA, Homogeneity Level.

  • Abstract

    This paper explores the enhancement of clustering techniques through the integration of preprocessing methods and nature-inspired algorithms. Achieving perfection in making clusters from the given dataset is a crucial task. Many algorithms have ‎been proposed in the literature to make useful clusters of raw data. But due to the day-by-day changing properties and ‎complexity of data, like multidimensional data values, increasing size, and many more parameters, they still require lots of ‎enhancements in clustering techniques. By addressing the limitations of traditional clustering approaches, the research ‎emphasizes the importance of pre-processing methodologies like PCA and KNN to improve clustering outcomes. ‎The limitation of handling high-dimensional data by an optimizer algorithm is addressed by PCA, which improves feature examination of ‎the dataset at a low level for further processes. Additionally, it examines various nature-inspired algorithms that can be applied to ‎clustering tasks, demonstrating their efficacy in optimizing and refining clustering results. Overall, the study presents a ‎framework combining KNN+PCA+EGWO that combines these elements to achieve superior clustering performance, i.e., ‎increasing the result performance by 45-50 % and the effects of preprocessing steps are also shown with low error and other ‎great parameters present in the paper‎.

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  • How to Cite

    Yadav, S. S., & Sutaria, K. . (2025). PCA-Based Model to Enhance The Performance of Data‎Clustering Using A Metaheuristic Algorithm. International Journal of Basic and Applied Sciences, 14(5), 282-288. https://doi.org/10.14419/gcjafw37