手法を比較

	著者の帰属推定（文体測定学）	ベイズ因子検定
分野	テキストマイニング	ベイズ
系統	Machine learning	Bayesian methods
提唱年	2009	1961
提唱者	Mosteller & Wallace; Stamatatos	Harold Jeffreys
種類	Supervised stylometric classification	Bayesian hypothesis comparison
原典	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
別名	Stylometry, Authorship Analysis, Yazarlık Atıfı, Authorship Identification	bayes factor, BF10, Bayesian hypothesis test, Bayes Faktörü — Hipotez Testi
関連	3	3
概要	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.