An ad rem Unsupervised Classification Review

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TypeTechnical Report
Subjectpattern recognition; unsupervised learning; clustering
AbstractA brief survey of some unsupervised learning and clustering algorithms is performed based on a classical pattern recognition book. Other unsupervised approaches are also briefly introduced in order to broaden the content of the survey of such a large body of possible approaches. An example from paleontology is used to motivate the unsupervised learning problem, while examples from proteomics, geophysical prospecting and digital remote sensing are very briey mentioned. In addition, an unsupervised learning procedure (theIsodata clustering algorithm) was implemented and results reported.
Publication date
LanguageEnglish
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number48807
NPARC number8914451
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Record identifier955317dc-b33a-4806-b054-4bf0240b13ea
Record created2009-04-22
Record modified2016-05-09
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