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Finding Churn Trend Scenario Using ML Techniques

C.P. Maheswaran, Chris Chettissery



 Media transmission and in addition the network access suppliers assumes an essential part in the mobile communications and the data society. Telecom segment is consistently developing with its progression in highlights and innovation. Consumer loyalty is an imperative factor which chooses the execution of firms. Customer churn expectation is an essential technique in CRM (Customer Relationship Management), knowing the churn propensity appeared by the customers helps to take better upgrades to keep up the clients, which are the jewel or asset relating to an organization. There are a few data mining procedures accessible like Decision Tree, Logistic Regression, Random Forest and Support Vector Machines. This paper presents diverse machine learning algorithms foreseeing churn and found that Gradient Boosting Classifier performs superior to all other algorithms compared with Future exploration issues are likewise further more discussed.

Key words: SVM, Decision Tree, Random Forest, Machine Learning, Churn Prediction

Cite this Article

C.P. Maheswaran, Chris Chettissery. Finding Churn Trend Scenario Using ML Techniques. Journal of Telecommunication, Switching Systems and Networks. 2019; 6(1): 1–7p.

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