Editing Factor analysis (section)

==== Bayesian methods ====

By placing a [[Prior probability|prior distribution]] over the number of latent factors and then applying Bayes' theorem, Bayesian models can return a [[probability distribution]] over the number of latent factors. This has been modeled using the [[Indian buffet process]],<ref>{{cite book|author=Alpaydin|year=2020|title=Introduction to Machine Learning|edition=5th|pages=528–9}}</ref> but can be modeled more simply by placing any discrete prior (e.g. a [[negative binomial distribution]]) on the number of components.