Deep Forest-Based Intelligent Yield Predicting of Buchwald-Hartwig Coupling Reaction

Abstract

Buchwald-Hartwig coupling reaction is widely used in organic chemical synthesis, yield prediction is particularly important. In 2018, Science reported a yield prediction method based on random forest, but this method lacks feature learning. Therefore, an intelligent prediction and analysis method of coupling reaction yield based on deep forest is proposed. Combined with the advantages of deep learning and ensemble learning, the new deep model in the form of non-neural network is explored, which has good characterization learning ability and low difficulty in adjusting parameters, realizes the efficient prediction of chemical reaction, and analyzes the factors that have a significant impact on the prediction of reaction yield.