Highly versatile and accurate machine learning methods for predicting perovskite properties

A dataset of 3720 ABX3-type perovskites and 2660 A 2 B(I)B(II)X 6 -type double perovskites was collected and cleaned up to train a machine learning model that predicts features such as band gaps. SHAP interpretability analysis provides new insights for bandgap evaluation.