Fig. 4.

Predictor importance analysis and extinction probabilities of the resistant opportunistic pathogen population. Conditional predictor importance values are calculated over $\mathrm{5,000}$ samples and 200 trees and normalized between 0 and 1. Extinction probabilities are calculated using 600,000 randomly subsampled realizations, 1,200 realizations per $N=\left\{1,2,\dots ,20\right\}$ per $T_{df}=\left\{0,15,30,\dots ,360\right\}$ value. (A and B) Normalized conditional predictor importance values for (A) classification and (B) regression, for different values of number of treatment courses ($N$) varying from 1 to 20. (C) Extinction probability of the resistant pathogen population given the number of treatment courses ($N$) and the duration of drug-free period after last treatment ($T_{df}$). (D and E) Normalized conditional predictor importance values for (D) classification and (E) regression, for different values of total duration of all treatments (${\sum }_i{d}_i$) varying from 3 to 150 d. (F) Extinction probability of the resistant pathogen population given the total duration of all treatments (${\sum }_i{d}_i$) and the duration of drug-free period after last treatment ($T_{df}$). (G and H) Normalized conditional predictor importance values for (G) classification and (H) regression, for different values of the duration of drug-free period after last treatment ($T_{df}$) varying from 0 to 360 d. (I) Normalized conditional predictor importance values for classification and regression when all predictors are randomized.