Demystifying the Random Forest. Deconstructing and Understanding this…

In classical Machine Learning, Random Forests have been a silver bullet type of model. In this post, I want to better understand the components that make up a Random Forest. To accomplish this, I am going to deconstruct the Random Forest into its most basic components and explain what is going on in each level of computation. By the end, we will have attained a much deeper understanding of how Random Forests work and how to work with them with more intuition. The examples we will use will be focused on classification, but many of the principles apply to the regression scenarios as well. Let's start by invoking a classic Random Forest pattern.