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Using adaptively weighted large margin classifiers for robust sufficient dimension reduction

Artemiou, Andreas 2019. Using adaptively weighted large margin classifiers for robust sufficient dimension reduction. Statistics 53 (5) , pp. 1037-1051. 10.1080/02331888.2019.1636050
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Abstract

In this paper we combine adaptively weighted large margin classifiers with Support Vector Machine (SVM)-based dimension reduction methods to create dimension reduction methods robust to the presence of extreme outliers. We discuss estimation and asymptotic properties of the algorithm. The good performance of the new algorithm is demonstrated through simulations and real data analysis.

Item Type: Article
Date Type: Published Online
Status: Published
Schools: Mathematics
Advanced Research Computing @ Cardiff (ARCCA)
Subjects: Q Science > QA Mathematics
Publisher: Taylor & Francis
ISSN: 0233-1888
Date of First Compliant Deposit: 20 June 2019
Date of Acceptance: 19 June 2019
Last Modified: 18 Oct 2019 18:32
URI: http://orca.cf.ac.uk/id/eprint/123584

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