ABSTRACT The classification of functional data has many applications in a variety of problems. A popular method for functional data classification is based on distances of the observations to the class centroid. In this paper, we introduce a weighted version of the centroid classifier that is based on projection functions and can lead to asymptotically perfect classification. We select the projection functions so that they optimize classification performance. The superiority of the proposed method is shown by using a simulation study and two real data sets.

中文翻译：

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基于投影的功能数据分类

摘要 功能数据的分类在各种问题中有很多应用。功能数据分类的一种流行方法是基于观察到类质心的距离。在本文中，我们介绍了一种基于投影函数的质心分类器的加权版本，可以导致渐近完美的分类。我们选择投影函数，以便它们优化分类性能。通过使用模拟研究和两个真实数据集显示了所提出方法的优越性。