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Bayesian classification based on multivariate binary data

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dc.contributor.author Johnson, WO en
dc.contributor.author Kokolakis, GE en
dc.date.accessioned 2014-03-01T01:09:44Z
dc.date.available 2014-03-01T01:09:44Z
dc.date.issued 1994 en
dc.identifier.issn 0378-3758 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/11168
dc.subject Dirichlet distribution en
dc.subject entropy en
dc.subject kernel estimate en
dc.subject predictive density en
dc.subject.classification Statistics & Probability en
dc.subject.other CATEGORICAL-DATA en
dc.subject.other KERNEL METHOD en
dc.subject.other DISCRIMINATION en
dc.title Bayesian classification based on multivariate binary data en
heal.type journalArticle en
heal.identifier.primary 10.1016/0378-3758(94)90152-X en
heal.identifier.secondary http://dx.doi.org/10.1016/0378-3758(94)90152-X en
heal.language English en
heal.publicationDate 1994 en
heal.abstract Consider a disease which has associated with it d symptoms that are either present or absent. Several specific symptoms are known for an individual. The question is whether the person has the disease? This is a classification problem based on multivariate binary data. Our approach is Bayesian and involves the prediction of future d-vectors of binary responses. Underlying this problem is the implicit estimation of the corresponding 2d cell probabilities. This is difficult with low structure and with moderate or large d, unless the sample sizes for the training data are enormous. Our model incorporates a prior distribution on unknown parameters, and a 'smoothing' parameter that relates the cells to one another. The posterior is approximated in order to obtain cell probability estimates and an approximate predictive density. Consistency results are indicated, and the procedure is illustrated with data involving the diagnosis of a disease called 'dry eyes'. © 1994. en
heal.publisher ELSEVIER SCIENCE BV en
heal.journalName Journal of Statistical Planning and Inference en
dc.identifier.doi 10.1016/0378-3758(94)90152-X en
dc.identifier.isi ISI:A1994PA44700002 en
dc.identifier.volume 41 en
dc.identifier.issue 1 en
dc.identifier.spage 21 en
dc.identifier.epage 35 en


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