Four model classes for efficient Bayesian selection

T.J. Tjalkens

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review


I consider a binary classification problem with a feature vector of high dimensionality. Spam mail filters are a popular example hereof. A Bayesian approach requires us to estimate the probability of a feature vector given the class of the object. Due to the size of the feature vector this is an unfeasible t ask. A useful approach is to split the feature space into several (conditionally) independent subspaces. This results in a new problem, namely how to find the " best" subdivision. In this paper I consider a weighing approach that will perform (asymptotically) as good as the best subdivision and still has a manageable complexity
Originele taal-2Engels
TitelProceedings of the 29th Symposium on Information Theory in the Benelux, May 29-30, 2008, Leuven, Belgium
RedacteurenL. Perre, Van der, A. Dejonghe, V. Ramon
Plaats van productieLeuven
ISBN van geprinte versie978-90-9023135-8
StatusGepubliceerd - 2008


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