Analysis of Customer Churn Prediction in Telecom Industry Using Logistic Regression

K. Sandhya Rani; Shaik Thaslima; N.G.L. Prasanna; R.Vindhya; P. Srilakshmi

doi:10.21276/ijircst.2021.9.4.6

Abstract

Customers plays an import role in industry to run industry. Churn of the customer may lead many consequences. Customer churn prediction must the important aspect of any company. This helps in the detection of customers who are likely to cancel a subscription to a service. Recently, the mobile telecommunication market has changed from a rapidly growing market into a state of saturation The focus of telecommunication companies is to shift from growing of large customer into keeping customers in house. For that reason, it is valuable to know which customers are likely to switch to a competitor in future. the model is proposed for churn prediction for telecommunication companies using machine learning techniques namely logistic regression. A comparison is done on the efficiency of the algorithm on the available dataset.

Keywords

Machine learning, logistic regression, variance reduction, Bayesian Models, CRM (Customer Relationship Management)

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Cites this article as

[K. Sandhya Rani, Shaik Thaslima, N.G.L. Prasanna, R.Vindhya, P. Srilakshmi (2021), Analysis of Customer Churn Prediction in Telecom Industry Using Logistic Regression, International Journal of Innovative Research in Computer Science and Technology (IJIRCST), Vol-9, Issue-4, Page No-27-29], (ISSN 2347 - 5552). www.ijircst.org

Corresponding Author

K. Sandhya Rani

Assistant Professor, Department of Computer Science and Engineering, Dhanekula Institute of Engineering and Technology, Vijayawada, Andhra Pradesh, India

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