Nilam Nur Amir, Sjarif and Muhammad Rusydi, Mohd Yusof and Doris Hooi, Ten Wong and Suraya, Ya’akob and Roslina, Ibrahim and Mohd Zamri, Osman (2019) A Customer Churn Prediction using Pearson Correlation Function and K Nearest Neighbor Algorithm for Telecommunication Industry. International Journal of Advances in Soft Computing & Its Applications, 11 (2). pp. 46-59. ISSN 2074-8523. (Published)
|
Pdf
A Customer Churn Prediction using Pearson.pdf Download (1MB) | Preview |
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: | Customer Churn Prediction, Pearson Correlation, Machine Learning, K Nearest Neighbor. |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Faculty/Division: | Faculty of Computer System And Software Engineering |
| Depositing User: | Noorul Farina Arifin |
| Date Deposited: | 14 Aug 2019 03:52 |
| Last Modified: | 14 Aug 2019 03:52 |
| URI: | http://umpir.ump.edu.my/id/eprint/25630 |
| Download Statistic: | View Download Statistics |
Actions (login required)
 |
View Item |