Figure 2

Training and cross-validation (CV) errors of the multivariate models. Minimum training errors (solid circles) of (a) multiple linear regressions (MLRs), (b) regression trees (RTs), and (c) artificial neural networks (ANNs) in the first CV training set decreased, while the CV errors [open squares; Equation (4)] reached the minimum (light-dotted arrows) at the subset size of 2 in (a), 2 in (b), and 5 in (c). The most parsimonious model (dark-solid arrows) within one standard error of the model with the minimum error was the model with 1 predictor for (a), 2 predictors for (b) and 4 predictors for (c). (The cross-validated variance of TY, for reference, is 1.43 ± 0.13).