Machine Learning Basics - Random Forest

RF is based on decision trees. In machine learning decision trees are a technique for creating predictive models. They are called decision trees because the prediction follows several branches of "if… then…" decision splits - similar to the branches of a tree. If we imagine that we start with a sample, which we want to predict a class for, we would start at the bottom of a tree and travel up the trunk until we come to the first split-off branch. This split can be thought of as a feature in machine learning, let's say it would be "age"; we would now make a decision about which branch to follow: "if our sample has an age bigger than 30, continue along the left branch, else continue along the right branch".