decision trees

xgboost feature importance

This post will go over extracting feature (variable) importance and creating a function for creating a ggplot object for it. I will draw on the simplicity of Chris Albon’s post. For steps to do the following in Python, I recommend his post. If you’ve ever created a decision tree, you’ve probably looked at measures of feature importance. In the above flashcard, impurity refers to how many times a feature was use and lead to a misclassification.