. The test error for predicting melting points was further analyzed using a scatter plot in Fig. ) for trends in absolute and percentage error respectively with the ground truth value. It was found that the machine learning model overpredicts at lower temperature and underpredicts at higher temperature. Additionally, Fig. ) shows that the model performance improves with the increase in temperature. This could be simply because we had more diverse and higher quantity of training data for higher temperature substances. It was also found that models underperform predicting melting points when Si, B and P are present (Fig. in supplementary material shows the definition of the top features those are reported in SHAP analysis.