Explaining Predictions: Random Forest Post-hoc Analysis (randomForestExplainer package)

Recap This is a continuation on the explanation of machine learning model predictions. Specifically, random forest models. We can depend on the random forest package itself to explain predictions based on impurity importance or permutation importance. Today, we will explore external packages which aid in explaining random forest predictions. External packages There are external a few packages which offer to calculate variable importance for random forest models apart from the conventional measurements found within the random forest package.