• Savita

The telecom sector is vigorous with recent technologies and current resources in today’s time. In telecommunication, the customers have different types of options. Customers have a lot of complaints like customers call drop-in particular area, issues related with customer bills, disconnection complaints, issues with promotions, call timing issues, complaint related to resolve duration call delayed problems, quality of services problems and coverage related complaints, churn prediction problem. But now a day’s churn prediction for customers is an in telecommunication. In this review paper complete focus is on, how to develop a classification model, to handle the customer complaints in telecommunication. This work introduced churn prediction model for customers in telecommunication using data mining classification methods. Various classifiers have used in telecommunication for churn prediction of customers. Classification algorithms comparison depends upon efficiency of the available dataset. Different data mining-based classifiers namely decision tree, KNN, logistic regression, SVM, naive Bayes and rule based and random forest are used to handle customer complaints. The performance of classification model is measured with different performance measures like accuracy, recall and precision measures with confusion matrices.

Telecommunication, Churn Prediction, CRM, Classification techniques, Discussion and performance, Conclusion

"Classification Methods in Telecommunication for Churn Prediction of Customers: A Novel Approach Using Data Mining", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.150-159, June 2019, Available :http://www.jetir.org/papers/JETIR1907A46.pdf

"Classification Methods in Telecommunication for Churn Prediction of Customers: A Novel Approach Using Data Mining", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp150-159, June 2019, Available at : http://www.jetir.org/papers/JETIR1907A46.pdf