利用各种机器学习技术预测电信行业的客户流失预测

A. Gaur, R. Dubey
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引用次数: 13

摘要

电信行业的客户流失分析与预测是当今的一个问题,因为分析各种客户的行为,预测哪些客户即将离开电信公司的订阅,对电信行业来说非常重要。因此,在当今的商业环境下,数据挖掘技术和算法对公司来说起着重要的作用,因为获得新客户的成本超过了保留现有客户的成本。在本文中,我们可以专注于预测客户流失的各种机器学习技术,通过这些技术我们可以建立分类模型,如逻辑回归,支持向量机,随机森林和梯度提升树,并比较这些模型的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting Customer Churn Prediction In Telecom Sector Using Various Machine Learning Techniques
Customer churn analysis and prediction in telecom sector is an issue now a days because it’s very important for telecommunication industries to analyze behaviors of various customer to predict which customers are about to leave the subscription from telecom company. So data mining techniques and algorithm plays an important role for companies in today’s commercial conditions because gaining a new customer’s cost is more than retaining the existing ones. In this paper we can focuses on various machine learning techniques for predicting customer churn through which we can build the classification models such as Logistic Regression, SVM, Random Forest and Gradient boosted tree and also compare the performance of these models.
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