论文标题
基于索博的指数的无监督能力识别方法
An unsupervised capacity identification approach based on Sobol' indices
论文作者
论文摘要
在许多排名问题中，应在汇总过程中考虑解决情况的某些特定方面。一个例子是标准之间存在相关性，这可能会引入派生排名中的偏见。在这些情况下，可以使用基于容量的聚合函数来克服这种不便，例如Choquet积分或多线性模型。采用此类策略需要一个阶段来估计这些聚合操作员的参数。在我们没有有关这些参数的更多信息或决策者给出的偏好的情况下，此任务可能很困难。因此，本文的目的是通过基于多线性模型的无监督方法来处理此类情况。我们的目标是估算一个能够减轻决策数据中相关性引入的偏见，因此提供更公平结果的能力。通过合成数据的数值实验证明了我们的提案的生存能力
In many ranking problems, some particular aspects of the addressed situation should be taken into account in the aggregation process. An example is the presence of correlations between criteria, which may introduce bias in the derived ranking. In these cases, aggregation functions based on a capacity may be used to overcome this inconvenience, such as the Choquet integral or the multilinear model. The adoption of such strategies requires a stage to estimate the parameters of these aggregation operators. This task may be difficult in situations in which we do not have either further information about these parameters or preferences given by the decision maker. Therefore, the aim of this paper is to deal with such situations through an unsupervised approach for capacity identification based on the multilinear model. Our goal is to estimate a capacity that can mitigate the bias introduced by correlations in the decision data and, therefore, to provide a fairer result. The viability of our proposal is attested by numerical experiments with synthetic data
