Application of Multivariate Adaptive Regression Splines (MARSplines) for Predicting Hansen Solubility Parameters Based on 1D and 2D Molecular Descriptors Computed from SMILES String

Figure 2

The correlation between experimental and computed values of parameter d prediction is done using Eq. (1). The quality of the chosen optimal d(25, 2) model is characterized by the fitting criteria: R² = 0.9470, (R_adj)² = 0.9378, LOF = 0.3680, K_xx = 0.4341, RMSE_tr = 0.4293, MAE_tr = 0.3239, F = 103.3872, and N = 130, and fulfils the following internal validation criteria: (Q_loo)² = 0.8601, RMSE_cv = 0.6973, and MAE_cv = 0.4309 [71, 72].