Sample selection from a given dataset to validate machine learning models - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2021

Sample selection from a given dataset to validate machine learning models

Résumé

The selection of a validation basis from a full dataset is often required in industrial use of supervised machine learning algorithm. This validation basis will serve to realize an independent evaluation of the machine learning model. To select this basis, we propose to adopt a "design of experiments" point of view, by using statistical criteria. We show that the "support points" concept, based on Maximum Mean Discrepancy criteria, is particularly relevant. An industrial test case from the company EDF illustrates the practical interest of the methodology.
Fichier principal
Vignette du fichier
hal_iooss.pdf (121.06 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03208245 , version 1 (26-04-2021)

Identifiants

Citer

Bertrand Iooss. Sample selection from a given dataset to validate machine learning models. 50th Meeting of the Italian Statistical Society (SIS2021), Jun 2021, Pisa, Italy. ⟨hal-03208245⟩

Collections

CNRS EDF
55 Consultations
139 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More