Shrinking the Tube: A New Support Vector Regression Algorithm

A new algorithm for Support Vector regression is described. For a priori chosen 1/, it automatically adjusts a flexible tube of minimal radius to the data such that at most a fraction 1/ of the data points lie outside. More(cid: 173) over, it is shown how to use parametric tube shapes with non-constant radius. The algorithm is analysed theoretically and experimentally.

Authors

• Bernhard Schölkopf
• Peter Bartlett
• Alex Smola
• Robert Williamson

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