Predicting Loan Credit Risk using Apache Spark Machine Learning Random Forests

Let's go through an example of Credit Risk for Bank Loans: Decision trees create a model that predicts the class or label based on several input features. Decision trees work by evaluating an expression containing a feature at every node and selecting a branch to the next node based on the answer. A possible decision tree for predicting Credit Risk is shown below. The feature questions are the nodes, and the answers "yes" or "no" are the branches in the tree to the child nodes. Our data is from the German Credit Data Set which classifies people described by a set of attributes as good or bad credit risks.