applied to the occurrence
rate model to determine presence/absence (binary) estimates has been
replaced with a separate binary classification model. This model is
extremely similar to the occurrence rate model, but instead of
estimating probability of occurrence on a scale of 0-1, this version of
random forest predicts a binary 0 or 1 for each prediction (checklist or
prediction grid cell). Our implementation of this model uses the same
feature set, factor handling, and balanced sampling as the occurrence
r