Leveraging Machine Learning Algorithms for predicting Churn in Telecom industries

Customers are essential to the operation of business. Customer churn can have a variety of effects. Predicting customer attrition must be a key component of every business. This aids in identifying clients who are about to end their subscription to a service. The mobile telecom market recently transitioned from being one that was expanding quickly to one that was saturated. The goal of telecommunications firms is to shift their attention from attracting new, large customers to maintaining existing ones. Knowing which clients are likely to switch to a competitor in the future is important because of this. The model machine learning methods(classifiers) like logistic regression, decision tree, gaussian classifier, random forest classifier, polynomial kernel SVM support vector Machine) classifier, RBF (Radial basis Function) kernel SVM classifier, Sigmoid kernel SVM classifiers for churn prediction for telecommunications firms. On the supplied data set, a comparison of the algorithms' works effectiveness is made.