The goal of this post is to teach python programmers why they must have balanced data for model training and how to balance those data sets. Often times, in machine learning classification problems, models will not work as well and be incomplete without performing data balancing on train data. This post will serve as an end-to-end guide for solving this problem. Table of contents Before running a model, you need to fit the model on a set of data that is distinct from the data you test it on.
