Variables selected in five fold cross-validation (CV) for the models. Variables (X1 to X12) are plotted versus model subset size (p). Counts of the selected variables in five-fold cross-validation for (a) multiple linear regressions (MLRs), (b) regression trees (RTs), and (c) artificial neural networks (ANNs) as subset size, p, increases from 1 to 12 along x-axis. The darker the color the more often a variable (y-axis) was selected for a model with a given number of independent variables (x-axis). Light-dotted and dark-solid arrows indicate the models with minimum errors and the most parsimonious models within one standard error of the minimum, respectively, as in Figure 2.