Abstract
This chapter describes the Support Vector technique for function estimation problems such as pattern recognition, regression estimation, and solving linear operator equations. It shows that for the Support Vector method both the quality of solution and the complexity of the solution does not depend directly on the dimensionality of an input space. Therefore, on the basis of this technique one can obtain a good estimate using a given number of high-dimensional data.
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Vapnik, V. (1998). The Support Vector Method of Function Estimation. In: Suykens, J.A.K., Vandewalle, J. (eds) Nonlinear Modeling. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5703-6_3
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DOI: https://doi.org/10.1007/978-1-4615-5703-6_3
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-7611-8
Online ISBN: 978-1-4615-5703-6
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