Figure 1

Variable importance of predictors of Ucrit according to the random forest model. Variable importance is the difference in prediction accuracy (i.e. the number of observations classified correctly) before and after permuting a variable, averaged over all trees123; and represents the effect of a variable in both main effects and interactions. Total percentage of explained variation was 72.8%. Figure created using R120.