Which machine learning algorithm should I use? The ML Algorithm cheat sheet helps you choose the best machine learning algorithm for your predictive analytics solution. Your decision is driven by both the nature of your data and the goal you want to achieve with your data. What do you want to do with your data? I must state here that we need to have a solid understanding of the iterative system of methods that guide Data Scientists on the ideal approach to solving problems using the Data Science Methodology.

Now, that we know the basic building blocks of a decision tree, we need to know how to grow one. Creating a decision tree describes the process of dividing the input space into several distinct, non-overlapping sub-spaces. In order to divide the input space, we have to test all features and threshold values to find the optimal split that minimizes our cost function. Once we obtain the best split, we can continue to grow our tree recursively. The process is termed recursive since each sub-space may be split an indefinite number of times until a stopping criterion (e.g.