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Introduction to Kernel Methods: Classification of Multivariate Data

Fauvel, Mathieu Introduction to Kernel Methods: Classification of Multivariate Data. (2016) EAS Publications Series, 77. 171-193. ISSN 1633-4760

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Official URL: http://dx.doi.org/10.1051/eas/1677008

Abstract

In this chapter, kernel methods are presented for the classification of multivariate data. An introduction example is given to enlighten the main idea of kernel methods. Then emphasis is done on the Support Vector Machine. Structural risk minimization is presented, and linear and non-linear SVM are described. Finally, a full example of SVM classification is given on simulated hyperspectral data.

Item Type:Article
Additional Information:Thanks to EDP Sciences editor. The definitive version is available at https://www.eas-journal.org The original PDF of the article can be found at EAS Journal website : https://www.eas-journal.org/articles/eas/pdf/2016/01/eas1677008.pdf
ProdINRA Id:355938
Audience (journal):National peer-reviewed journal
Institution:French research institutions > Institut National de la Recherche Agronomique - INRA (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
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Deposited On:15 Jun 2017 08:16

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