Universiti Teknologi Malaysia Institutional Repository

A customer churn prediction using pearson correlation function and k nearest neighbor algorithm for telecommunication industry

Sjarif, N. N. A. and Yusof, M. R. M. and Wong, D. H. T. and Ya'akob, S. and Ibrahim, R. and Osman, M. Z. (2019) A customer churn prediction using pearson correlation function and k nearest neighbor algorithm for telecommunication industry. International Journal of Advances in Soft Computing and its Applications, 11 (2). pp. 46-59. ISSN 2074-8523

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Abstract

Customer churn in telecommunication industry is actually a serious issue. The Telco company needs to have a churn prediction model to prevent their customer from moving to another telco. Therefore, the objective of this paper is to propose the customer churn prediction using Pearson Correlation and K Nearest Neighbor algorithm. The algorithm is validated via training and testing dataset with the ratio 70:30. Based on experiment, the result shows that the K Nearest Neighbor algorithm performs well compared to the others with the accuracy for training is 80.45% and testing 97.78%.

Item Type:Article
Uncontrolled Keywords:k nearest neighbor, machine learning, pearson correlation
Subjects:T Technology > T Technology (General)
Divisions:Razak School of Engineering and Advanced Technology
ID Code:89617
Deposited By: Narimah Nawil
Deposited On:09 Feb 2021 05:01
Last Modified:09 Feb 2021 05:01

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