Knowledge based proximal support vector machines |
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Authors: | Reshma Khemchandani Jayadeva Suresh Chandra |
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Institution: | 1. Department of Mathematics, Indian Institute of Technology, Hauz Khas, New Delhi 110016, India;2. Department of Electrical Engineering, Indian Institute of Technology, Hauz Khas, New Delhi 110016, India |
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Abstract: | We propose a proximal version of the knowledge based support vector machine formulation, termed as knowledge based proximal support vector machines (KBPSVMs) in the sequel, for binary data classification. The KBPSVM classifier incorporates prior knowledge in the form of multiple polyhedral sets, and determines two parallel planes that are kept as distant from each other as possible. The proposed algorithm is simple and fast as no quadratic programming solver needs to be employed. Effectively, only the solution of a structured system of linear equations is needed. |
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Keywords: | Quadratic programming Proximal support vector machines Pattern classification Knowledge based systems Polyhedral sets |
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