Data downloaded from IBM Sample Data Sets for customer retention programs. The goal of this work is to create an analysis in order to predict consumer behaviour. The project is subdivided in the following steps:
- Data Preparation
- EDA
- Models:
- Logistic Regression
- Decision Tree (LOOCV, K-fold crossvalidation, validation approach)
- Baggin tree
- Random Forest
- XGBoost
- Conclusions
The report file contains a detailed explanation of the various procedures, what has been done, the structure of the models and the conclusions regarding the results we have obtained.