40 Algorithms Every Programmer Should Know

Training a random forest algorithm

In training, this algorithm takes N samples from the training data and creates m subsets of our overall data. These subsets are created by randomly selecting some of the rows and columns of the input data. The algorithm builds m independent decision trees. These classification trees are represented by C₁ to C_m.