Issoglio, E orcid.org/0000-0003-3035-2712, Smith, P orcid.org/0000-0002-1200-678X and Voss, J orcid.org/0000-0002-2323-3814 (2021) On the Estimation of Entropy in the FastICA Algorithm. Journal of Multivariate Analysis, 181. 104689. ISSN 0047-259X
Abstract
The fastICA method is a popular dimension reduction technique used to reveal patterns in data. Here we show both theoretically and in practice that the approximations used in fastICA can result in patterns not being successfully recognised. We demonstrate this problem using a two-dimensional example where a clear structure is immediately visible to the naked eye, but where the projection chosen by fastICA fails to reveal this structure. This implies that care is needed when applying fastICA. We discuss how the problem arises and how it is intrinsically connected to the approximations that form the basis of the computational efficiency of fastICA.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Approximation; Blind source separation; Convergence; Counterexample; FastICA; Independent component analysis; Projection pursuit; Projections |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 23 Sep 2020 08:58 |
Last Modified: | 25 Jun 2023 22:25 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.jmva.2020.104689 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:165782 |