Comparer des méthodes

	Attribution d'auteur (Stylométrie)	Test du facteur de Bayes
Domaine	Fouille de textes	Bayésien
Famille	Machine learning	Bayesian methods
Année d'origine	2009	1961
Auteur d'origine	Mosteller & Wallace; Stamatatos	Harold Jeffreys
Type	Supervised stylometric classification	Bayesian hypothesis comparison
Source fondatrice	Stamatatos, E. (2009). A survey of modern authorship attribution methods. Journal of the American Society for Information Science and Technology, 60(3), 538–556.	Jeffreys, H. (1961). Theory of Probability (3rd ed.). Clarendon Press / Oxford University Press. ISBN: 978-0198503682
Alias	Stylometry, Authorship Analysis, Yazarlık Atıfı, Authorship Identification	bayes factor, BF10, Bayesian hypothesis test, Bayes Faktörü — Hipotez Testi
Apparentées	3	3
Résumé	Authorship attribution is the task of identifying the most probable author of an anonymous or disputed text by analysing its stylistic fingerprint. Rooted in the statistical work of Mosteller and Wallace on the Federalist Papers (1964), the field was systematically surveyed and formalised by Stamatatos (2009), who catalogued feature sets ranging from character n-grams and function-word frequencies to syntactic and semantic representations used by modern machine-learning classifiers.	The Bayes factor test, formalised by Harold Jeffreys in 1961, is a Bayesian method for comparing two competing hypotheses. Rather than returning a binary reject/retain verdict, it produces a continuous ratio BF₁₀ that quantifies how much more (or less) probable the data are under the alternative hypothesis H₁ than under the null hypothesis H₀.