Vector Machines (SVM), Gaussian Process Regression (GPR, RBF + white kernel), Random Forest Regression (RFR), and Gradient Boosting Regression (GBR). All were driven on the scikit-learn (1.2.2) module. Ridge and Lasso used the RidgeCV and LassoCV classes to optimize the regularization term automatically. Other models, less influenced by hyperparameters, were operated with default settings.