A Machine Learning Model for Customer Churn Prediction using CatBoost Classifier

Quality of Service (QoS) is now attracting an increasing number of clients towards a company. Meanwhile, the ability to provide clients with technologically better QoS is highly demanding in recent times. ON the other hand, effective customer interactions may assist the organization to gain new clients, retain existing ones, and improve customer retention by bringing in more income. This research study has used Cat Boost Classifier to predict the customer behavior, retain the customers and increase the company’s benefit. The proposed model provides a prediction accuracy of 95%, when compared with the existing methods.