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Support Vector Classification

In: Forecasting and Hedging in the Foreign Exchange Markets

Author

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  • Christian Ullrich

    (BMW AG)

Abstract

Computational geometry is the branch of computer science that studies algorithms for solving geometric problems. The input to a computational-geometry problem is typically a description of a set of geometric objects, such as a set of points, a set of line segments, or the vertices of a polygon. The output is a response to a query about these objects (such as whether any of the lines intersect), or even a new geometric object (such as a convex hull or a separating hyperplane). The problem under consideration is the linear separability problem [112]. In the special case of finding whether two sets of points in general space can be separated, the linear separability problem becomes the binary classification problem (BCP). The most general form of the BCP is the case of whether two sets of points in general space can be separated by k hyperplanes.

Suggested Citation

  • Christian Ullrich, 2009. "Support Vector Classification," Lecture Notes in Economics and Mathematical Systems, in: Forecasting and Hedging in the Foreign Exchange Markets, chapter 9, pages 65-82, Springer.
    • Handle: RePEc:spr:lnechp:978-3-642-00495-7_9
    DOI: 10.1007/978-3-642-00495-7_9
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