Predicting Customer Churn Prediction In Telecom Sector Using Various Machine Learning Techniques

Abstract

Customer churn analysis and prediction in telecom sector is an issue now a days because it's very important for telecommunication industries to analyze behaviors of various customer to predict which customers are about to leave the subscription from telecom company. So data mining techniques and algorithm plays an important role for companies in today's commercial conditions because gaining a new customer's cost is more than retaining the existing ones. In this paper we can focuses on various machine learning techniques for predicting customer churn through which we can build the classification models such as Logistic Regression, SVM, Random Forest and Gradient boosted tree and also compare the performance of these models.