3 ways to design effective classes in ML Classification Algorithms

In this post we are going to see three ways to affectively design the target classes in classification problems using the properties of the training data alone.

Background

Classification is an area in Machine Learning (ML) where the machine is tasked to learn to categorize a given input. For example, given an image, the machine should return the category the image belongs to.