Generating additive clustering models with minimal stochastic complexity.

DOI10.1007/s00357-001-0033-yzbMath1040.91085OpenAlexW2088487363WikidataQ57710725 ScholiaQ57710725MaRDI QIDQ1566091

Michael D. Lee

Publication date: 2002

Published in: Journal of Classification (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00357-001-0033-y

zbMATH Keywords

additive clusteringoverlapping clusteringstochastic complexity

Mathematics Subject Classification ID

Clustering in the social and behavioral sciences (91C20)

Related Items (5)

Prototypes, exemplars and the response scaling parameter: a Bayes factor perspective ⋮ Regarding the complexity of additive clustering models: comment on Lee (2001). ⋮ A tutorial on Bayes factor estimation with the product space method ⋮ Latent Features in Similarity Judgments: A Nonparametric Bayesian Approach ⋮ On the computation of entropy prior complexity and marginal prior distribution for the Bernoulli model

This page was built for publication: Generating additive clustering models with minimal stochastic complexity.