Ordinal Regression with K-SVCR Machines
Ordinal Regression with K-SVCR Machines
复制标题
使用 K-SVCR 机器进行序数回归
DOI：
10.1007/3-540-45720-8_79
复制
发表时间：
2001
期刊：
影响因子：
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通讯作者：
Andreu Català
中科院分区：
文献类型：
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作者：
C. Angulo;Andreu Català
序数回归问题或排序具有分类和回归问题的混合特征，因此它可以被视为一个独立的问题类。处理此类问题的学习机器应该明确考虑此类问题的特定行为。在本文中，排序问题是从最近定义的基于支持向量的学习架构（K-SVCR 学习机，专门开发用于处理多个类别）的角度来阐述的。在本研究中，其定义与文献中的其他现有结果进行了比较。
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, theK-SVCR learning machine, specially developed to treat with multiple classes. In this study its definition is compared to other existing results in the literature.