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Cost-based reweighting for Principal Lq SVM for sufficient dimension reduction

Artemiou, Andreas 2019. Cost-based reweighting for Principal Lq SVM for sufficient dimension reduction. Journal of Mathematics and Statistics

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Abstract

In this work we try to address the imbalance of the number of points which naturally occurs when slicing the response in Sufficient Dimension Reduction methods (SDR). Specifically, some recently proposed support vector machine based (SVM-based) methodology suffers a lot more due to the properties of the SVM algorithm. We target a recently proposed algorithm called Principal LqSVM and we propose the reweighting based on a different cost. We demonstrate that our reweighted proposal works better than the original algorithm in simulated and real data.

Item Type: Article
Status: In Press
Schools: Mathematics
Subjects: Q Science > QA Mathematics
Publisher: Science Publications
ISSN: 1549-3644
Date of First Compliant Deposit: 30 August 2019
Date of Acceptance: 20 August 2019
Last Modified: 30 Aug 2019 10:45
URI: http://orca.cf.ac.uk/id/eprint/125171

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