Time to retire F1-binary score for action unit detection.
Action units
Data imbalance
F1 score
Machine learning
Journal
Pattern recognition letters
ISSN: 0167-8655
Titre abrégé: Pattern Recognit Lett
Pays: Netherlands
ID NLM: 9879988
Informations de publication
Date de publication:
Jun 2024
Jun 2024
Historique:
medline:
1
8
2024
pubmed:
1
8
2024
entrez:
1
8
2024
Statut:
ppublish
Résumé
Detecting action units is an important task in face analysis, especially in facial expression recognition. This is due, in part, to the idea that expressions can be decomposed into multiple action units. To evaluate systems that detect action units, F1-binary score is often used as the evaluation metric. In this paper, we argue that F1-binary score does not reliably evaluate these models due largely to class imbalance. Because of this, F1-binary score should be retired and a suitable replacement should be used. We justify this argument through a detailed evaluation of the negative influence of class imbalance on action unit detection. This includes an investigation into the influence of class imbalance in train and test sets and in new data (i.e., generalizability). We empirically show that F1-micro should be used as the replacement for F1-binary.
Identifiants
pubmed: 39086494
doi: 10.1016/j.patrec.2024.04.016
pmc: PMC11290352
doi:
Types de publication
Journal Article
Langues
eng
Pagination
111-117Déclaration de conflit d'intérêts
Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.