标题： 设计特征向量表示：来自化学的一个案例研究 显示英文标题

标题： Designing Feature Vector Representations: A case study from Chemistry

摘要： 我们提出一个案例研究，探讨在分析化学多变量集合数据的背景下特征描述符。每个集合成员的数据包括三部分：每个集合成员的设计参数、来自数值模拟的现场数据以及分子的物理性质。由于基于特征的方法有可能降低数据复杂性并促进比较和聚类，我们专注于这些方法。然而，设计特征向量表示有许多选项，并没有明显的偏好。为了更好地理解不同的表示方式，我们分析了它们的相似性和差异性。因此，我们关注从表示中得出的三个特性：成对距离的分布、聚类倾向以及成对距离的排名顺序。我们调查的结果部分确认了预期的行为，但也提供了一些令人惊讶的观察结果，这些观察结果可用于化学领域特征表示的未来发展。 显示英文摘要

摘要： We present a case study investigating feature descriptors in the context of the analysis of chemical multivariate ensemble data. The data of each ensemble member consists of three parts: the design parameters for each ensemble member, field data resulting from the numerical simulations, and physical properties of the molecules. Since feature-based methods have the potential to reduce the data complexity and facilitate comparison and clustering, we are focusing on such methods. However, there are many options to design the feature vector representation and there is no obvious preference. To get a better understanding of the different representations, we analyze their similarities and differences. Thereby, we focus on three characteristics derived from the representations: the distribution of pairwise distances, the clustering tendency, and the rank-order of the pairwise distances. The results of our investigations partially confirmed expected behavior, but also provided some surprising observations that can be used for the future development of feature representations in the chemical domain.