RandomForest , XGBoost and Ensemble models to predict bad loans
A British challenger bank collected data about the performance of their loans issued from 2009 to 2015. They would like to use the data to build a model to help their credit analysts assess new loan applications, i.e. predict if a loan would be repaid in full or defaulted on. The loans.csv dataset contains ~230k examples and 31 different variables. A description of these variables is provided in data-dictionary.csv.