Credit Risk Binary Classification

Project Description

In this project my team and I performed a case study analyzing the performance of different classification algorithms against loan risk data.
We explored the impact of an unbalanced data set to the performance of the models.
Additionaly, we compared the difference between Hold-out and Cross-Validation method for splitting the testing and training partitions, as well as different split percentages.