Predicting whether a customer will exit the bank's service using multiple Machine Learning models. The original dataset is retrieved from Kaggle Customer Churn Dataset.
This repository includes:
- README.md
- LICENSE
- Customers-Churn-Data-Prediction-Model.ipybn: To see interactive plot, please access the NBViewer.
What are includes in the project?
- Data Extraction and Cleaning
- Exploratory Data Analysis
- Build Prediction Model
- Feature Engineering
- Prediction Model with/without Hyperparameters Tuning.
Eventually, using Random Forest Classifer, as well as two other options (Decision Tree Classifier and Support Vector Classifier), I can reach an accuracy rate of 87% - 88%.