A MCMC Approach to Hierarchical Mixture Modelling.

Christopher K.I. Williams

A MCMC Approach to Hierarchical Mixture Modelling.

Christopher K.I. Williams

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

There are many hierarchical clustering algorithms available, but these lack a firm statistical basis. Here we set up a hierarchical probabilistic mixture model, where data is generated in a hierarchical tree-structured manner. Markov chain Monte Carlo (MCMC) methods are demonstrated which can be used to sample from the posterior distribution over trees containing variable numbers of hidden units.

Original language	English
Title of host publication	Advances in Neural Information Processing Systems 12 (NIPS 1999)
Publisher	MIT Press
Pages	680-686
Number of pages	7
Publication status	Published - 1999

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title = "A MCMC Approach to Hierarchical Mixture Modelling.",

abstract = "There are many hierarchical clustering algorithms available, but these lack a firm statistical basis. Here we set up a hierarchical probabilistic mixture model, where data is generated in a hierarchical tree-structured manner. Markov chain Monte Carlo (MCMC) methods are demonstrated which can be used to sample from the posterior distribution over trees containing variable numbers of hidden units.",

author = "Williams, \{Christopher K.I.\}",

year = "1999",

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pages = "680--686",

booktitle = "Advances in Neural Information Processing Systems 12 (NIPS 1999)",

publisher = "MIT Press",

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PY - 1999

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AB - There are many hierarchical clustering algorithms available, but these lack a firm statistical basis. Here we set up a hierarchical probabilistic mixture model, where data is generated in a hierarchical tree-structured manner. Markov chain Monte Carlo (MCMC) methods are demonstrated which can be used to sample from the posterior distribution over trees containing variable numbers of hidden units.

M3 - Conference contribution

SP - 680

EP - 686

BT - Advances in Neural Information Processing Systems 12 (NIPS 1999)

PB - MIT Press

ER -

A MCMC Approach to Hierarchical Mixture Modelling.

Abstract

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