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	Inférence bayésienne	Système de classement Elo
Domaine	Statistique	Prise de décision
Famille	Bayesian methods	Regression model
Année d'origine	1763	1978
Auteur d'origine	Thomas Bayes; Pierre-Simon Laplace	Arpad Elo
Type	Probabilistic inference paradigm	Pairwise comparison ranking model
Source fondatrice	Bayes, T. (1763). An essay towards solving a problem in the doctrine of chances. Philosophical Transactions of the Royal Society of London, 53, 370–418.	Elo, A. E. (1978). The Rating of Chessplayers, Past and Present. Arco Publishing. ISBN: 978-0-668-04721-0
Alias	Bayes inference, Bayesian statistics, Bayesian updating, posterior inference	Elo Rating System, Elo Chess Rating, Elo Skill Rating, Elo Derecelendirme Sistemi
Apparentées	3	2
Résumé	Bayesian inference is a statistical paradigm in which probability represents degrees of belief rather than long-run frequencies. It encodes prior knowledge about parameters in a prior distribution, combines that prior with the likelihood of observed data via Bayes' theorem, and produces a posterior distribution that quantifies updated uncertainty. The foundational theorem was published posthumously by Thomas Bayes in 1763 and subsequently systematized by Pierre-Simon Laplace in his 1812 Théorie analytique des probabilités.	The Elo Rating System is a pairwise comparison-based ranking method developed by Hungarian-American physicist and chess master Arpad Elo and formally published in 1978. Originally designed to assess the relative skill levels of chess players, it assigns each competitor a numerical rating that rises or falls after each encounter based on the expected versus actual outcome. The system assumes that player performance follows a logistic distribution, enabling probabilistic predictions of match results and continuous rating refinement over time.