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- Title
A Customer Churn Prediction using Pearson Correlation Function and K Nearest Neighbor Algorithm for Telecommunication Industry.
- Authors
Sjarif, Nilam Nur Amir; Yusof, Muhammad Rusydi Mohd; Hooi-Ten Wong, Doris; Ya'akob, Suraya; Ibrahim, Roslina; Osman, Mohd Zamri
- 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%.
- Subjects
CUSTOMER retention; K-nearest neighbor classification; PEARSON correlation (Statistics); TELECOMMUNICATION; PREDICTION models; CONSUMERS; CONSUMER behavior
- Publication
International Journal of Advances in Soft Computing & Its Applications, 2019, Vol 11, Issue 2, p46
- ISSN
2710-1274
- Publication type
Article