Predictive Classification and Bayesian Inference

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Title: Predictive Classification and Bayesian Inference
Author: Xiong, Jie
Contributor: University of Helsinki, Faculty of Science, Department of Mathematics and Statistics
Publisher: Helsingin yliopisto
Date: 2015-06-15
Language: en
Thesis level: Doctoral dissertation (article-based)
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.
Subject: statistics
Rights: This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.

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