Machine Learning Assisted Prediction Of Organic Salt Structure Properties

This article discusses the use of random forest models to extend the ability of models to crystals with different chemical compositions. The models are tested by incorporating structures from an extension CSP run into the training sets and evaluating their performance. The article also explores methods for minimizing training errors in the random forest regressor model.