Predictors of surgical re-intervention: Variable importance
The AUC was used to quantify the importance of the predictor. For each
RF model, the AUC was calculated on the test set. Then the same was done
after permuting each predictive variable. By calculating the difference
between the permuted and non-permuted AUC, the importance of each
individual predictor can be quantified. The difference in AUC for the
different predictors in the optimized model were in ascending order of
importance: 0.005 for parity, 0.017 for previous caesarean section,
0.019 for age, 0.026 for dysmenorrhea and 0.051 for duration of
menstruation. This means dysmenorrhea and duration of menstruation have
the highest impact on the AUC of the RF model.