Machine learning for chemistry requires a strategy for representing (featurizing) molecules. In this issue of Chem, Sandfort et al. describe an approach that concatenates 24 fingerprint representations into 71,375-dimensional vectors, which are then used for a variety of supervised learning tasks related to chemical reactivity.

中文翻译：

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分子表示法：在指纹上花很长时间

化学的机器学习需要一种表示（特征化）分子的策略。在本期Chem中，Sandfort等人。描述一种将24个指纹表示连接到71,375维向量的方法，然后将其用于与化学反应性有关的各种监督学习任务。