Abstract
In this article, with the aim to avoid the loss of information that occurs in the usual one-versus-one SVM decomposition procedure of the two-phases (decomposition, reconstruction) multi-classification scheme tri-class SVM approach is addressed. As the most relevant result, it will be demonstrated the robustness improvement of the proposed scheme based on tri-class machine versus that based on the bi-class machine.
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Angulo, C., González, L., Català, A., Velasco, F. (2007). Multi-classification with Tri-class Support Vector Machines. A Review. In: Sandoval, F., Prieto, A., Cabestany, J., Graña, M. (eds) Computational and Ambient Intelligence. IWANN 2007. Lecture Notes in Computer Science, vol 4507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73007-1_34
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DOI: https://doi.org/10.1007/978-3-540-73007-1_34
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