Fig. 2. Visual representation of different machine learning algorithms. (a) Support Vector Machines aim to draw an optimal decision boundary between two categories. (b) Random Forest models build multiple decision trees based on a subset of variables and data. This average of the decision trees is used as the final prediction. (c) Neural Networks transform the input as it passes through the hidden layers. These transformations should allow the network to make accurate classification in the output layer.