Using data about the default of credit cards of real clients, the goal is to inspect, analyze and perform techniques in order to get hidden information and transform this information into knowledge that could be used in a real project. In addition to that at the end of a project we should be able to predict payment capability of a client, whether he/she can pay next month or not.
The steps are written in R script and results are interpreted in report.
Decision Trees: Accuracy of 81.4%
Random Forest with 100 trees: Accuracy of 81.6%
Official data set can be found on: https://archive.ics.uci.edu/ml/datasets/default+of+credit+card+clients