Sample selection from a given dataset to validate machine learning models - Archive ouverte HAL Access content directly
Conference Papers Year : 2021

Sample selection from a given dataset to validate machine learning models

Abstract

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
Origin Files produced by the author(s)

Dates and versions

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

Identifiers

Cite

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
59 View
154 Download

Altmetric

Share

Gmail Mastodon Facebook X LinkedIn More