IJIREM

Abstract

In today's highly competitive marketplace, especially for businesses, retaining loyal customers is becoming increasingly challenging.In one scenario, losing a customer results in a loss of profits for the telecom industry's expansion, while in another, the cost of acquiring new customers is significantly higher than the cost of maintaining existing ones; in this critical scenario, the telecom industry ought to concentrate on maintaining existing customers.This project will use supervised machine learning algorithms, primarily Linear Discriminant Analysis, Support Vector Machine, K Nearest Neighbor, and Random Forest, to analyze the open dataset of customer data and predict customer stress.

Keywords

Support Vector Machine, K-Nearest Neighbor, Linear Discriminant Analysis, One Hot Encoding.

Reference

Tou, J. T., & Gonzalez, R. C. (1974). Pattern recognition principles. Addison-Wesley.
Van den Poel, D., &Larivie‘re, B. (2004). Customer attrition analysis for ï¬nancial services using proportional hazard models. European Journal of Operational Research, 157, 196–217.
Wei, C. P., & Chiu, I. T. (2002). Turning telecommunications call details to churn prediction: A data mining approach. Expert Systems with Applications, 23, 103–112.
Wong, B. K., Bodnovich, T. A., &Selvi, Y. (1997). Neural network applications in business: a review and analysis of the literature (1988–1995). Decision Support Systems, 19, 301–320.
Zhan, G., Patuwo, B. E., & Hu, M. Y. (1998). Forecasting with artiï¬cial neural network: The state of the art. International Journal of Forecasting, 14, 35–62.
Zhang, X., Edwards, J., & Harding, J. (2007). Personalised online sales using web usage data mining. Computers in Industry, 58, 772–782.
Berry, M. J. A., &Linoff, G. S. (2003). Data mining techniques: For marketing, sales, and customer support. John Wiley & Sons.
Buckinx, W., & Van den Poel, D. (2005). Customer base analysis: partial defection of behaviourally loyal clients in a non-contractual FMCG retail setting. European Journal of Operational Research, 164(1), 252–268.
Burez, J., & Van den Poel, D. (2007). Crm at a pay-TV company: Using analytical models to reduce customer attrition by targeted marketing for subscription services. Expert Systems with Applications, 32, 277–288.
Chiang, D. A., Wang, Y. F., Lee, S. L., & Lin, C. J. (2003). Goal-oriented sequential pattern for network banking churn analysis. Expert Systems with Applications, 25, 293–302.
Coussement, K., & Van den Poel, D. (2008). Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques. Expert Systems with Applications, 34, 313–327. Cybenco, H. (1998). Approximation by super positions of sigmoidal.

Cites this article as

[D. Janardhan Reddy, V. Gopi Krishna, Sk. JIlani Basha, R. Pavan Kumar, K. Manohara Rao (2022), Customer Stress Prediction in Telecom Industry using Machine Learning, International Journal of Innovative Research in Engineering & Management (IJIREM), Vol-9, Issue-4, Page No-118-121], (ISSN 2347 - 5552). www.ijirem.org

Corresponding Author

D. Janardhan Reddy

Assistant Professor, Department of Computer Science & Engineering, PACE Institute of Technology & Sciences, Ongole, Andhra Pradesh, India

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