Thread: Though there is lots of community interest in model-agnostic model explanations (eg. LIME), I’ve been interested in an explainer specific to random forests. Came across a great one here: github.com/MI2DataLab/ran…#rstats
To begin, train an RF model and run the explain_forest() function. #rstats
Next thing you know, a variety of “views” into the forest appear on your machine. Can explore interactions between metrics and variables. For more details, check out this vignette: rawgit.com/MI2DataLab/ran…#rstats