Comment on "Predicting reaction performance in C-N cross-coupling using machine learning"

Abstract

Ahneman et al (Reports, 13 April 2018) applied machine learning models to predict C-N cross-coupling reaction yields. The models use atomic, electronic, and vibrational descriptors as input features. However, the experimental design is insufficient to distinguish models trained on chemical features from those trained solely on random-valued features in retrospective and prospective test scenarios, thus failing classical controls in machine learning.