A Customer Churn Prediction using Pearson Correlation Function and K Nearest Neighbor Algorithm for Telecommunication Industry
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...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Soft Computing Research Group, UTM Malaysia
2019
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/25630/ http://umpir.ump.edu.my/id/eprint/25630/ http://umpir.ump.edu.my/id/eprint/25630/1/A%20Customer%20Churn%20Prediction%20using%20Pearson.pdf |
| Summary: | 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%. |
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