摘要
为了研究运营商如何利用大数据的优势提高移动用户信用评估的科学性与准确性,基于熵值法和分类决策树模型,建立了移动用户信用评估模型,详细分析其实现原理,并给出实际应用场景。通过具体的应用,证明该模型能减少人工分析中更新计算公式的繁重工作量,高效、灵活、准确地完成用户信用预测评估工作,具有科学性和实用性。
In order to enhance the scientificity and accuracy of the credit evaluation of mobile communication customers based on data for operators, a credit evaluation model based on the entropy method and classification decision tree was proposed in this paper. Its basic principle was elaborated and the practical application scenarios were presented. It was proved by the concrete applications that the proposed model can reduce the heavy workload of updating calculation fomaula in the artificial analysis, and efficiently, flexibly and accurately complete the credit evaluation for mobile communication customers with scientificity and practicability.
作者
黄英持
郑婷婷
HUANG Yingchi ZHENG Tingting(China Mobile Guangdong Co., Ltd., Guangzhou 510623, China The Open University, of Guangdong, Guangzhou 510091, China)
出处
《移动通信》
2017年第11期85-89,共5页
Mobile Communications
关键词
信用评价
熵值法
分类决策树
credit evaluation entropy method classification decision tree