Predictive Classification and Bayesian Inference

Show simple item record Xiong, Jie 2015-05-13T05:41:50Z 2015-06-05 fi 2015-05-13T05:41:50Z 2015-06-15
dc.identifier.uri URN:ISBN:978-951-51-1244-6 fi
dc.description.abstract A general inductive probabilistic framework for clustering and classification is introduced using the principles of Bayesian predictive inference, such that all quantities are jointly modelled and the uncertainty is fully acknowledged through the posterior predictive distribution. Several learning rules have been considered and the theoretical results are extended to acknowledge complex dependencies within the datasets. Multiple probabilistic models have been developed for analysing data from a wide variate of fields of application. State-of-art algorithms are introduced and developed for the model optimization. en
dc.description.abstract fi
dc.format.mimetype application/pdf fi
dc.language.iso eng
dc.publisher Helsingin yliopisto fi
dc.publisher Helsingfors universitet sv
dc.publisher University of Helsinki en
dc.relation.isformatof URN:ISBN:978-951-51-1243-9 fi
dc.rights Julkaisu on tekijänoikeussäännösten alainen. Teosta voi lukea ja tulostaa henkilökohtaista käyttöä varten. Käyttö kaupallisiin tarkoituksiin on kielletty. fi
dc.rights This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited. en
dc.rights Publikationen är skyddad av upphovsrätten. Den får läsas och skrivas ut för personligt bruk. Användning i kommersiellt syfte är förbjuden. sv
dc.subject statistics fi
dc.title Predictive Classification and Bayesian Inference en
dc.type.ontasot Doctoral dissertation (article-based) en
dc.type.ontasot Artikkeliväitöskirja fi
dc.type.ontasot Artikelavhandling sv
dc.ths Corander, Jukka
dc.opn Frigessi, Arnoldo
dc.type.dcmitype Text
dc.contributor.organization University of Helsinki, Faculty of Science, Department of Mathematics and Statistics en
dc.contributor.organization Helsingin yliopisto, matemaattis-luonnontieteellinen tiedekunta, matematiikan ja tilastotieteen laitos fi
dc.contributor.organization Helsingfors universitet, matematisk-naturvetenskapliga fakulteten, institutionen för matematik och statistik sv
dc.type.publication doctoralThesis

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