fig5

Figure 5. (A) Heatmap of Pearson correlation coefficient matrix for the ΔG_CO- predicted optimal feature set; (B) Ranking of feature importance within the optimal feature set; (C-H) Predictive performance of various models trained using different ML methods. Copyright 2020, American Chemical Society, Reproduced with permission^[90]; (I and J) Feature importance of the top ten significant features predicted by GBR and XGBR models; (K) Utilizing SHAP analysis to consider the overall impact of different features on model prediction; (L) Predicting reaction free energy via the GBR model: excellent agreement between predicted values and DFT calculations. Copyright 2024, Elsevier, Reproduced with permission^[91]. ML: Machine learning; GBR: gradient boosting regression; XGBR: extreme gradient boosting regression; SHAP: Shapley Additive Explanations; DFT: density functional theory.