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IJSTR >> Volume 9 - Issue 4, April 2020 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Particle Swarm Optimization With Kernel Support Vector Machine For Churn Prediction In Telecommunication Industry

[Full Text]

 

AUTHOR(S)

Isabella Amali , Dr. R. Arunkumar

 

KEYWORDS

Churn prediction, Customer retention, Telecommunication, Optimization algorithm.

 

ABSTRACT

At present times, because of the challenges posed from global competitors, customer churn prediction (CCP) provides a major concern for organizations in different churns. To provide better customer retention, various CCP models have been presented. This paper presents a new CCP using hybridization of particle swarm optimization with kernel support vector machine (PSO-KSVM) in telecommunication industry. Here, PSO algorithm is used to optimize the variables of SVM namely C and σ. The validation of PSO-KSVM takes place using a benchmark dataset. The results ensured the effective outcome of the presented model over the compared methods.

 

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