Pr{\'e}diction optimale pour un mod{\`e}le ordinal {\`a} covariables fonctionnelles
Machine Learning
2025-06-24 v1
Abstract
We present a prediction framework for ordinal models: we introduce optimal predictions using loss functions and give the explicit form of the Least-Absolute-Deviation prediction for these models. Then, we reformulate an ordinal model with functional covariates to a classic ordinal model with multiple scalar covariates. We illustrate all the proposed methods and try to apply these to a dataset collected by EssilorLuxottica for the development of a control algorithm for the shade of connected glasses.
Keywords
Cite
@article{arxiv.2506.18615,
title = {Pr{\'e}diction optimale pour un mod{\`e}le ordinal {\`a} covariables fonctionnelles},
author = {Simón Weinberger and Jairo Cugliari and Aurélie Le Cain},
journal= {arXiv preprint arXiv:2506.18615},
year = {2025}
}
Comments
in French language, Journ{\'e}es de statistiques, Soci{\'e}t{\'e} Fran\c{c}aise des Statistiques, Jul 2023, Bruxelle- Universit{\'e} Libre de Bruxelles (ULB), Belgique