About this document
ROC Curve Analysis for Churn Prediction by Vijay rathod is a document available to read on EtoBox.
This document describes the process of building a machine learning model to predict customer churn for a telecommunications company. Various features of customer data are analyzed through plots and correlation analysis to understand relationships with churn. Highly correlated features are removed and SMOTE is used to balance the imbalanced data. Several models are trained and evaluated, with XGBoost achieving the highest accuracy of 98.31% on the test data based on confusion matrices and ROC curves. Finally
- Author
- Vijay rathod
- Language
- EN