Churn-Prediction-Project

In this project, a churn prediction model is developed for a private bank as a term project for Data Mining class.

Project includes extensive data preprocessing, feature engineering and ensemble machine learning implementations. In the imbalanced dataset, 0.90 ROC-AUC score is achieved. Features' roles in the prediction are explained through decision trees.

Please refer to following files for the code and presentation:

Code.ipynb

Presentation.pdf