A Nonparametric Bayesian Method for Inferring Features From Similarity Judgments


The additive clustering model is widely used to infer the features of a set of stimuli from their similarities, on the assumption that similarity is a weighted linear function of common features. This paper develops a fully Bayesian formulation of the additive clustering model, using methods from nonparametric Bayesian statistics to allow the number of… (More)


7 Figures and Tables