本文已被：浏览 1661次 下载 2142次
Received:November 25, 2018 Revised:December 12, 2018
Received:November 25, 2018 Revised:December 12, 2018
中文摘要: 运用群决策方法，对随机森林、神经网络、梯度提升树三种算法所生成的个体学习器进行集成，构建基于群决策的P2P借贷信用风险评估模型.选取人人贷、拍拍贷的数据进行实验研究，结果显示，集成模型的风险评估效果较个体学习器有所提升，且优于传统的逻辑回归方法.
Abstract:In this study, we propose a combination approach based on group decision-making method, using random forest, neural network and GBDT as individual learners, to assess credit risk of borrowers in P2P lending. To validate the proposed method, two real-world datasets from PPDai.com and renrendai.com are examined. The results show that, compared with the individual learners, the proposed method has made a better performance.
文章编号： 中图分类号： 文献标志码：
基金项目:国家自然科学基金面上项目（71571175）
引用文本：
姜雪莹,秦进.基于群决策的P2P借贷信用风险评估.计算机系统应用,2019,28(5):226-231
JIANG Xue-Ying,QIN Jin.Group Decision-Making Method for Credit Risk Assessment in P2P Lending.COMPUTER SYSTEMS APPLICATIONS,2019,28(5):226-231
姜雪莹,秦进.基于群决策的P2P借贷信用风险评估.计算机系统应用,2019,28(5):226-231
JIANG Xue-Ying,QIN Jin.Group Decision-Making Method for Credit Risk Assessment in P2P Lending.COMPUTER SYSTEMS APPLICATIONS,2019,28(5):226-231
