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首页> 外文期刊>International Journal of Advances in Soft Computing and Its Applications >A Customer Churn Prediction using Pearson Correlation Function and K Nearest Neighbor Algorithm for Telecommunication Industry
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A Customer Churn Prediction using Pearson Correlation Function and K Nearest Neighbor Algorithm for Telecommunication Industry

机译：基于Pearson相关函数和K最近邻算法的电信行业客户流失预测

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摘要

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%.
机译：电信行业的客户流失实际上是一个严重的问题。电信公司需要具有客户流失预测模型，以防止其客户转移到另一家电信公司。因此，本文的目的是提出使用Pearson相关和K最近邻算法的客户流失预测。通过训练和测试数据集以70:30的比例验证该算法。实验结果表明，K最近邻算法与其他算法相比具有较好的性能，训练精度为80.45％，测试精度为97.78％。

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