A tutorial on support vector regression
Alex Smola and Bernhard Schölkopf
Statistics and Computing Volume 14, Number 3, pp. 199-222, 2004.

Abstract

In this tutorial we give an overview of the basic ideas under- lying Support Vector (SV) machines for function estimation. Furthermore, we include a summary of currently used algo- rithms for training SV machines, covering both the quadratic (or convex) programming part and advanced methods for dealing with large datasets. Finally, we mention some modifi- cations and extensions that have been applied to the standard SV algorithm, and discuss the aspect of regularization from a SV perspective.

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