Skip navigation
Skip navigation

Bayesian Estimation of the number of principal components

Seghouane, Abd-Krim; Cichocki, Andrzej

Description

Recently, the technique of principal component analysis (PCA) has been expressed as the maximum likelihood solution for a generative latent variable model. A central issue in PCA is choosing the number of principal components to retain. This can be considered as a problem of model selection. In this paper, the probabilistic reformulation of PCA is used as a basis for a Bayasian approach of PCA to derive a model selection criterion for determining the true dimensionality of data. The proposed...[Show more]

CollectionsANU Research Publications
Date published: 2006
Type: Conference paper
URI: http://hdl.handle.net/1885/30657
Source: European Signal Processing Conference Proceedings

Download

File Description SizeFormat Image
01_Seghouane_Bayesian_Estimation_of_the_2006.pdf93.43 kBAdobe PDF    Request a copy


Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.

Updated:  12 November 2018/ Responsible Officer:  University Librarian/ Page Contact:  Library Systems & Web Coordinator