Many decision problems in a variety of fields such as marketing, quality prediction, and economics correspond to the sorting decision problematic where an ordinal scale is used to express a preference of objects. Both Multiple Criteria Decision Aid and Statistical Learning fields offer methodologies to represent the preference of the decision maker facing the sorting problem, however, there are differences in terminology, objectives, key assumptions, and solution philosophies. In this context, this paper aims to explain these differences as well as similarities and connections between these two fields by reviewing exemplary methodologies in sorting problems. As we discuss, there are significant research opportunities for developing new methodologies by exploiting the strong aspects of these two fields.

中文翻译：

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排序问题中的偏好建模：多标准决策辅助和统计学习视角

市场营销、质量预测和经济学等各个领域的许多决策问题都对应于排序决策问题，其中使用序数尺度来表达对象的偏好。多标准决策辅助和统计学习领域都提供了方法来表示面临排序问题的决策者的偏好，但是在术语、目标、关键假设和解决方案哲学方面存在差异。在此背景下，本文旨在通过回顾分类问题的示例性方法来解释这两个领域之间的这些差异以及相似之处和联系。正如我们所讨论的，通过利用这两个领域的强大方面来开发新方法有重要的研究机会。