This tutorial explains how to generate feature importance plots from catboost using tree-based feature importance, permutation importance and shap.
During this tutorial you will build and evaluate a model to predict arrival delay for flights in and out of NYC in 2013.
This tutorial uses:
Open a new Jupyter notebook and import the following:
The data is from rdatasets imported using the Python package statsmodels.
As this model will predict arrival delay, the Null values are caused by flights did were cancelled or diverted. These can be excluded from this analysis.
SHAP contains a function to plot this directly.