Customer Churn Analysis in Telecom Sector using Machine Learning

With the speedy improvement of telecommunication industry, the carrier companies are willing extra toward growth of the subscriber base. To meet the want of surviving withinside the aggressive environment, the retention of current clients has turn out to be a large challenge. In the survey accomplished withinside the Telecom industry, it's miles said that the value of obtaining a brand new patron is a long way extra that preserving the present one. Therefore, with the aid of using amassing know-how from the telecom industries can assist in predicting the affiliation of the clients as whether or not or now no longer they'll depart the company. The required movement desires to be undertaken with the aid of using the telecom industries on the way to provoke the purchase in their related clients for making their marketplace price stagnant. Our paper proposes a brand new framework for the churn prediction version and implements it the usage of the WEKA Data Mining software. The performance and the overall performance of Decision tree and Logistic regression strategies were compared. In this version, we used a Decision Tree, Random Forest, and XGBoost.