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Customers Churn Prediction Model Comprising of Clustering and Classification: An Application of Improvised Kmeans Clustering Algorithm and Non Linear Support Vector Machine

Journal: International Journal of Computer Science and Mobile Computing - IJCSMC (Vol.9, No. 1)

Publication Date:

Authors : ; ;

Page : 107-115

Keywords : data mining; customer churn; clustering; k-means; classification; non-linear support vector machine;

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Customer churn is a significant issue that is regularly related with the existence cycle of the business. At the point when the business is in a development period of its life cycle, deals are expanding exponentially and the quantity of new clients to a great extent dwarfs the quantity of churners. On the other side, organizations in a develop period of in their life cycle, set their attention on lessening the rate of customer churn. This research work proposes an efficient computational intelligence model comprising of clustering achieved through improvised K-Means algorithm and classification achieved through Non Linear Support Vector Machine.

Last modified: 2020-01-27 00:33:01