Publications by authors named "Alisha Sikri"
Article Synopsis
- - The study emphasizes the importance of retaining existing customers over acquiring new ones, focusing on predicting customer churn using machine learning algorithms to enhance retention strategies.
- - It introduces a Ratio-based data balancing technique to effectively handle skewed customer churn data, significantly improving the accuracy of various predictive models, including ensemble algorithms like Gradient Boosting and XGBoost.
- - Results from testing several algorithms on balanced datasets show that the proposed method outperforms traditional data resampling techniques, with the best outcomes when using XGBoost in a 75:25 ratio setting, showcasing its effectiveness in predicting customer churn.
