“…From the literature review [20][21][22][23], branch and bound, sequential selection, mutual information (MI), Minimum Redundancy Maximum Relevance (mRMR), and evolutionary approaches such as Particle Swarm Optimization (PSO), have been implemented for optimized feature selection. The branch and bound method adopts monotonicity assumptions when searching for the optimal feature subset, whereas sequential selection that adds or removes one feature at a time is computationally expensive [20].…”