Figure 2 : Random-Forest Approximate Bayesian Computation
model-choice cross-validation. Heat map of the out-of-bag
cross-validation results considering each 10,000 simulations per each
nine competing models (Figure 1 , Table 1 ) in turn as
pseudo-observed target for RF-ABC model-choice. Prior probability of
correctly choosing a given scenario is 11%. Out-of-bag prior error rate
is 32.41%. RF-ABC model-choice performed using 1,000 decision trees and
24 summary-statistics (see Materials and Methods ).