Statistical methods used by most morphologists to validate species boundaries (such as principal component analysis [PCA] and non‐metric multidimensional scaling [nMDS]) are limiting because these methods are mostly used as visualization methods, and because the groups are identified by taxonomists (i.e., supervised), adding human bias. Here, we use a spectral clustering algorithm for the unsupervised discovery of species boundaries followed by the analysis of the cluster‐defining characters.

中文翻译：

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Hedychium 属的物种复杂界定：一种用于簇发现的机器学习方法。


大多数形态学家用来验证物种边界的统计方法（例如主成分分析 [PCA] 和非度量多维尺度 [nMDS]）是有限的，因为这些方法主要用作可视化方法，并且因为这些类群是由分类学家识别的。即监督），增加了人为偏见。在这里，我们使用谱聚类算法来无监督地发现物种边界，然后分析聚类定义特征。