EAOA: An Enhanced Archimedes Optimization Algorithm for Feature Selection in Classification

Feature selection plays a crucial role in order to mitigate the high dimensional feature space in different classification problems. The computational cost is reduced, and the accuracy of the classification is improved by reducing the dimension of feature space. Hence, in the classification task, finding the optimal subset of features is of utmost importance. Metaheuristic techniques have proved their efficacy in solving many real-world optimization issues. One of the recently introduced physics-inspired optimization methods is Archimedes Optimization Algorithm (AOA). This paper proposes an Enhanced Archimedes Optimization Algorithm (EAOA) by adding a new parameter that depends on the step length of each individual while revising the individual location. The EAOA algorithm is proposed to improve the AOA exploration and exploitation balance…