The ordinal regression problem or ordination have mixed features of both, the classification and the regression problem, so it can be seen as an independent problem class. The particular behaviour of this sort of problem should be explicitly considered by the learning machines working on it. In this paper the ordination problem is fomulated from the viewpoint of a recently defined learning architecture based on support vectors, the K-SVCR learning machine, specially developed to treat with multiple classes. In this study its definition is compared to other existing results in the literature. © Springer-Verlag Berlin Heidelberg 2001.
CITATION STYLE
Angulo, C., & Català, A. (2001). Ordinal regression with K-SVCR machines. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2084 LNCS, pp. 661–668). Springer Verlag. https://doi.org/10.1007/3-540-45720-8_79
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