Comparer des méthodes

	Système de classement Elo	Régression logistique	Le modèle de Plackett-Luce
Domaine	Prise de décision	Statistiques de recherche	Prise de décision
Famille	Regression model	Process / pipeline	Regression model
Année d'origine	1978	1958	1975
Auteur d'origine	Arpad Elo	David Roxbee Cox	Robin Plackett; R. Duncan Luce
Type	Pairwise comparison ranking model	Method	Probabilistic ranking model
Source fondatrice	Elo, A. E. (1978). The Rating of Chessplayers, Past and Present. Arco Publishing. ISBN: 978-0-668-04721-0	Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242.	Plackett, R. L. (1975). The analysis of permutations. Journal of the Royal Statistical Society: Series C, 24(2), 193–202.
Alias	Elo Rating System, Elo Chess Rating, Elo Skill Rating, Elo Derecelendirme Sistemi	logit model, binomial logistic regression, LR	Luce's Choice Axiom Model, Rank-Ordered Logit Model, Exploded Logit Model, Sıralama Tercih Modeli
Apparentées	2	3	3
Résumé	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.	Logistic regression is a statistical method for modeling the probability of a binary outcome (disease present/absent, success/failure) as a function of continuous and categorical predictors. Developed by David Roxbee Cox (1958), it solves the problem of predicting categorical outcomes by applying a logistic transformation to constrain predictions to the [0,1] probability interval, enabling accurate risk stratification, diagnostic prediction, and causal inference in epidemiology, medicine, and social science.	The Plackett-Luce model is a probabilistic framework for analysing and predicting rank-ordered data. Introduced by Robin Plackett (1975) — building on R. Duncan Luce's earlier axiom of choice (1959) — it models the probability of any complete ranking of items as a sequential selection process, where each item's chance of being chosen at each position is proportional to its latent worth parameter. It is widely used in preference learning, recommender systems, and choice modelling.