Comparative Analysis of Support Vector Machines Based on Linear and Quadratic Optimization Criteria

ICMLA, pp. 288-293, 2009.

Cited by: 2|Bibtex|Views2|DOI:https://doi.org/10.1109/ICMLA.2009.52
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Other Links: dblp.uni-trier.de|dl.acm.org|academic.microsoft.com

Abstract:

We present results from a comparative empirical study of two methods for constructing support vector machines (SVMs). The first method is the conventional one based on the quadratic programming approach, which builds the optimal separating hyperplane maximizing the margin between two classes (SVM-Q). The second method is based on the line...More

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