Artemiou, Andreas ORCID: https://orcid.org/0000-0002-7501-4090 and Shu, Min 2014. A cost based reweighted scheme of Principal Support Vector Machine. Akritas, Michael G., Lahiri, S. N. and Politis, Dimitris N., eds. Topics in Nonparametric Statistics, Springer Proceedings in Mathematics & Statistics, Springer, (10.1007/978-1-4939-0569-0_1) |
Official URL: http://link.springer.com/chapter/10.1007/978-1-493...
Abstract
Principal Support Vector Machine (PSVM) is a recently proposed method that uses Support Vector Machines to achieve linear and nonlinear sufficient dimension reduction under a unified framework. In this work, a reweighted scheme is used to improve the performance of the algorithm. We present basic theoretical results and demonstrate the effectiveness of the reweighted algorithm through simulations and real data application.
Item Type: | Book Section |
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Date Type: | Publication |
Status: | Published |
Schools: | Mathematics |
Subjects: | Q Science > QA Mathematics |
Publisher: | Springer |
ISBN: | 978-1-4939-0568-3 |
Last Modified: | 28 Oct 2022 09:54 |
URI: | https://orca.cardiff.ac.uk/id/eprint/76049 |
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