Response to Comment on "Predicting reaction performance in C-N cross-coupling using machine learning".
Journal:
Science (New York, N.Y.)
Published Date:
Nov 16, 2018
Abstract
We demonstrate that the chemical-feature model described in our original paper is distinguishable from the nongeneralizable models introduced by Chuang and Keiser. Furthermore, the chemical-feature model significantly outperforms these models in out-of-sample predictions, justifying the use of chemical featurization from which machine learning models can extract meaningful patterns in the dataset, as originally described.