Multi-objective Binary Coordinate Search for Feature Selection

arXiv:2402.12616v1 Announce Type: new
Abstract: A supervised feature selection method selects an appropriate but concise set of features to differentiate classes, which is highly expensive for large-scale datasets. Therefore, feature selection should aim at both minimizing the number of selected features and maximizing the accuracy of classification, or any other task. However, this crucial task is computationally highly demanding on many real-world datasets and requires a very efficient algorithm to reach a set of optimal features with a limited number …

abstract accuracy aim arxiv binary classification cs.lg cs.ne datasets feature features feature selection multi-objective scale search set type