Mike Keiser and Kangway Chuang publish a Technical Comment in Science

In their Technical Comment on “Predicting reaction performance in C–N cross-coupling using machine learning (Reports, 13 April 2018),” Kangway Chuang, Postdoctoral Fellow in the Keiser Lab, and Mike Keiser, Assistant Professor In-Residence, report that Ahneman et al.'s “experimental design [was] 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.”

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