In the past years, several works were dealing with the use of Support Vector Machine (SVM) for classifying functional data. Here, we propose to give an overview of these works and to introduce a new result based on the use of smoothing conditions on the observed functions. The originality of this approach both lies in the fact that the consistency result allows to work with the derivatives of the function instead of the function itself but also that it is relative to the observed discretization and not to the entire knowledge of the functions.
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Rossi, F., Villa, N. (2008). Recent Advances in the Use of SVM for Functional Data Classification. In: Functional and Operatorial Statistics. Contributions to Statistics. Physica-Verlag HD. https://doi.org/10.1007/978-3-7908-2062-1_41
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DOI: https://doi.org/10.1007/978-3-7908-2062-1_41
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