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A. J Smola and B. Schölkopf (1998)

A Tutorial on Support Vector Regression

Royal Holloway College, NeuroCOLT Technical Report(NC-TR-98-030), University of London, UK.

This tutorial gives an overview of the basic ideas underlying Support Vector (SV) machines for regression and function estimation. Furthermore, it includes a summary of currently used algorithms for training SV machines, covering both the quadratic (or convex) programming part and advanced methods for dealing with large datasets. Finally, some modifications and extensions that have been applied to the standard SV algorithm are mentioned, and it discusses the aspect of regularization and capacity control from a SV point of view.

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