Churn-Model

A company X required a churn model to mitigate the monetary losses from discounts provided to customers.

Documentation

All the analysis is shown in an html file, the source code is on the jupyter notebook (.ipynb).

data was not uploaded for privacy matters

EDA

Categorical Variable Analysis

Numerical Variable Analysis

Histograms

Results

1. Logistic Regression

2. XGB Boost

3. Random Forest

4. KNN