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.
CITATION STYLE
Bayro-Corrochano, E., Arana-Daniel, N., & Refugio Vallejo-Gutiérres, J. (2004). Clifford support vector machines for classification. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 3070, pp. 9–16). Springer Verlag. https://doi.org/10.1007/978-3-540-24844-6_2
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