A simple example of ML classification, cross validation, and visualization of feature importances

Overview

Simple-Classifier

This is a basic example of how to use several different libraries for classification and ensembling, mostly with sklearn. Example assumes the use of a retail customer dataset where the user is targeting a binary variable for sale/no sale. I highly recommend running this in Jupyter Notebook or Lab, or potentially in Colab.

Some code was borrowed, with love, from the notebooks of the Kaggle community.

Note that at the time of this publishing, certain libraries used within are not available for Macs running the new M1 silicone processor.

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