Multilayer Perceptron with Functional Inputs: an Inverse Regression Approach
Résumé
Abstract. Functional data analysis is a growing research field as more and more practical applications involve functional data. In this paper, we focus on the problem of regression and classification with functional predictors: the model suggested combines an efficient dimension reduction procedure [functional sliced inverse regression, first introduced by Ferré & Yao (Statistics, 37, 2003, 475)], for which we give a regularized version, with the accuracy of a neural network. Some consistency results are given and the method is successfully confronted to real-life data.
Domaines
Statistiques [math.ST]
Origine : Fichiers produits par l'(les) auteur(s)