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Support Vector Classification

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Forecasting and Hedging in the Foreign Exchange Markets

Part of the book series: Lecture Notes in Economics and Mathematical Systems ((LNE,volume 623))

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.

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Correspondence to Christian Ullrich Dr. .

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© 2009 Springer-Verlag Berlin Heidelberg

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Ullrich, C. (2009). Support Vector Classification. In: Forecasting and Hedging in the Foreign Exchange Markets. Lecture Notes in Economics and Mathematical Systems, vol 623. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00495-7_9

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  • DOI: https://doi.org/10.1007/978-3-642-00495-7_9

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