Abstract
This paper introduces the Clifford Support Vector Machines as a generalization of the real- and complex- valued Support Vector Machines. The major advantage of this approach is that one requires only one CSVM which can admit multiple multivector inputs and it can carry multi-class classification. In contrast one would need many real valued SVMs for a multi-class problem which is time consuming.
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Bayro-Corrochano, E., Arana-Daniel, N., Vallejo-Gutiérres, J.R. (2004). Clifford Support Vector Machines for Classification. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds) Artificial Intelligence and Soft Computing - ICAISC 2004. ICAISC 2004. Lecture Notes in Computer Science(), vol 3070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24844-6_2
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DOI: https://doi.org/10.1007/978-3-540-24844-6_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22123-4
Online ISBN: 978-3-540-24844-6
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