论文标题
通过部分最小二乘方法在不同域上的多元功能数据分类
Classification of multivariate functional data on different domains with Partial Least Squares approaches
论文作者
论文摘要
当在不同域上定义了感兴趣的随机功能向量的元素时，请考虑多元功能数据的分类（监督学习）。在这种情况下，介绍了用于多元功能数据的PLS分类和基于树PLS的方法。从计算的角度来看，我们表明只能使用具有单变量功能数据的PLS方法来获得带有多元功能数据回归的PLS组件。这提供了一种替代方法来介绍用于多元功能数据的PLS算法。
Classification (supervised-learning) of multivariate functional data is considered when the elements of the random functional vector of interest are defined on different domains. In this setting, PLS classification and tree PLS-based methods for multivariate functional data are presented. From a computational point of view, we show that the PLS components of the regression with multivariate functional data can be obtained using only the PLS methodology with univariate functional data. This offers an alternative way to present the PLS algorithm for multivariate functional data.
