While this exhaustive search aims to identify regions of high predictive accuracy, the computational cost of exploring such a vast feature space poses a significant challenge. By leveraging FO process, we can efficiently navigate this search space, applying tailored optimization techniques to reduce the computational burden. This allows us to pinpoint the most relevant features, ultimately improving DNN's performance without being overwhelmed by the complexity of the feature combinations.