A new computationally efficient algorithm to solve Feature Selection for Functional Data Classification in high-dimensional spaces

arXiv:2401.05765v2 Announce Type: replace-cross
Abstract: This paper introduces a novel methodology for Feature Selection for Functional Classification, FSFC, that addresses the challenge of jointly performing feature selection and classification of functional data in scenarios with categorical responses and multivariate longitudinal features. FSFC tackles a newly defined optimization problem that integrates logistic loss and functional features to identify the most crucial variables for classification. To address the minimization procedure, we employ functional principal components and develop a new adaptive version of …

abstract algorithm arxiv categorical challenge classification cs.lg data data classification feature features feature selection functional methodology multivariate novel paper responses solve spaces stat.ml type