Wallace’s approach to unsupervised learning: the Snob program

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dc.contributor.authorJorgensen, Murray A.
dc.contributor.authorMcLachlan, Geoffrey J.
dc.date.accessioned2009-01-18T22:07:58Z
dc.date.available2009-01-18T22:07:58Z
dc.date.issued2008
dc.description.abstractWe describe the Snob program for unsupervised learning as it has evolved from its beginning in the 1960s until its present form. Snob uses the minimum message length principle expounded in Wallace and Freeman (Wallace, C.S. and Freeman, P.R. (1987) Estimation and inference by Compact coding. J. Roy. Statist. Soc. Ser. B, 49, 240–252.) and we indicate how Snob estimates class parameters using the approach of that paper. We will survey the evolution of Snob from these beginnings to the state that it has reached as described by Wallace and Dowe (Wallace, C.S. and Dowe, D.L. (2000) MMM mixture modelling of multi-state, Poisson, Von Mises Circular and Gaussian distributions. Stat. Comput., 10, 73–83.) We pay particular attention to the revision of Snob in the 1980s where definite assignment of things to classes was abandoned.en
dc.format.mimetypeapplication/pdf
dc.identifier.citationJorgensen, M.A. & McLachlan, G J. (2008). Wallace's approach to unsupervised learning: the snob program. The Computer Journal, 51(5), 571-578.en
dc.identifier.doi10.1093/comjnl/bxm121en
dc.identifier.urihttps://hdl.handle.net/10289/1799
dc.language.isoen
dc.publisherOxford University Pressen
dc.relation.isPartOfThe Computer Journalen_NZ
dc.relation.urihttp://comjnl.oxfordjournals.org/cgi/content/abstract/51/5/571en
dc.rightsThis article has been published in the journal: The Computer Journal. ©2008 the author retains copyright.en
dc.subjectstatisticsen
dc.subjectcomputer programen
dc.subjectEM algorithmen
dc.subjectminimum message lengthen
dc.subjectmixture modelen
dc.subjectcluster analysisen
dc.titleWallace’s approach to unsupervised learning: the Snob programen
dc.typeJournal Articleen
pubs.begin-page571en_NZ
pubs.elements-id33605
pubs.end-page578en_NZ
pubs.issue5en_NZ
pubs.volume51en_NZ
uow.identifier.article-no5en_NZ
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