• Kirti Malviya
• Syed Rameez Ali

Predicting customer churn in telecommunication industries becomes a most important topic for research in recent years. Because its helps in detecting which customer are likely to change or cancel their subscription to a service. Analysis of data which is extracted from telecom companies can helps to find the reasons of customer churn and also uses the information to retain the customers. So predicting churn is very important for telecom companies to retain their customers. 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 machine learning techniques for predicting customer churn through which we can build the classification models such as SVM and Random Forest and also compare the performance of these models.

Churn prediction, data mining, telecom system ,Customer retention, classification system, random forest, svm

"PREDICTING CUSTOMER CHURN PREDICTION IN TELECOM SECTOR USING SVM AND RANDOM FOREST", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.200-204, June-2019, Available :http://www.jetir.org/papers/JETIR1906B29.pdf

"PREDICTING CUSTOMER CHURN PREDICTION IN TELECOM SECTOR USING SVM AND RANDOM FOREST", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp200-204, June-2019, Available at : http://www.jetir.org/papers/JETIR1906B29.pdf