标题： 神经网络作为功能分类器 显示英文标题

标题： Neural Networks as Functional Classifiers

摘要： 近年来，预测方法领域出现了大量创新。 这可以从机器学习方法在各种分类竞赛中的相对主导地位中看出。 尽管这些算法在多变量问题上表现出色，但在函数数据分析领域却一直未得到应用。 我们将一些显著的深度学习方法扩展到函数数据领域，以解决分类问题。 我们在多个分类应用中突出了我们方法的有效性，例如光谱数据的分类。 此外，我们通过模拟研究展示了我们分类器的性能，在这些研究中，我们将我们的方法与其他传统分类方法和函数线性模型进行了比较。 显示英文摘要

摘要： In recent years, there has been considerable innovation in the world of predictive methodologies. This is evident by the relative domination of machine learning approaches in various classification competitions. While these algorithms have excelled at multivariate problems, they have remained dormant in the realm of functional data analysis. We extend notable deep learning methodologies to the domain of functional data for the purpose of classification problems. We highlight the effectiveness of our method in a number of classification applications such as classification of spectrographic data. Moreover, we demonstrate the performance of our classifier through simulation studies in which we compare our approach to the functional linear model and other conventional classification methods.