Greedy feature selection: Classifier-dependent feature selection via greedy methods

arXiv:2403.05138v1 Announce Type: cross
Abstract: The purpose of this study is to introduce a new approach to feature ranking for classification tasks, called in what follows greedy feature selection. In statistical learning, feature selection is usually realized by means of methods that are independent of the classifier applied to perform the prediction using that reduced number of features. Instead, greedy feature selection identifies the most important feature at each step and according to the selected classifier. In the paper, the …

abstract arxiv classification classifier cs.lg cs.na feature feature selection independent math.na ranking statistical stat.ml study tasks type via