• NIKHIL CHANDRAKAR

Feature Selection aims to locate the main data from a given arrangement of features. As this task can be viewed as an optimization problem, the combinatorial development of the potential arrangements might be in-practical for a comprehensive search. Feature selection can productively improve the precision of classification and diminish the estimation, storage and calculation demands, and hence it has been applied in research progressively. Metaheuristic algorithms are among the most impressive algorithms for feature selection. There are numerous points of interest that make these algorithms more helpful to take care of a wide scope of issues today. One of the significant favorable circumstances of metaheuristic algorithms is giving fast and effective solutions for huge and complicated problems. Metaheuristic algorithms are fundamentally used to explore search space to discover ideal solutions. In this work, an Arithmetic optimization algorithm is proposed for Feature selection which improves the classification accuracy and guarantees ideal size of feature subset.

AOA(Arithmetic optimization algorithm), Feature selection, metaheuristic algorithm

"FEATURE SELECTION USING AOA (ARITHMETIC OPTIMIZATION) ALGORITHM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 2, page no.d427-d459, February-2025, Available :http://www.jetir.org/papers/JETIR2502350.pdf

"FEATURE SELECTION USING AOA (ARITHMETIC OPTIMIZATION) ALGORITHM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 2, page no. ppd427-d459, February-2025, Available at : http://www.jetir.org/papers/JETIR2502350.pdf