Shrinking the Tube: A New Support Vector Regression Algorithm
Published 1 December 1998
Bernhard Schölkopf, Peter L. Bartlett, Alex Smola, Robert C. Williamson
Citations181
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Abstract
A new algorithm for Support Vector regression is described. For a priori chosen , it automatically adjusts a flexible tube of minimal radius to the data such that at most a fraction of the data points lie outside. Moreover, it is shown how to use parametric tube shapes with non-constant radius. The algorithm is analysed theoretically and experimentally.
Keywords
Computer Science
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