| 个人信用评估的加权组合预测模型 |
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| 引用本文： | 谢行恒,陈玉芳.个人信用评估的加权组合预测模型[J].技术经济与管理研究,2008(2):8-10. |
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| 作者姓名： | 谢行恒 陈玉芳 |
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| 作者单位： | 1. 宁波工程学院经济与管理学院,浙江,宁波,315211
2. 杭州电子科技大学软件职业技术学院,浙江,杭州,310012 |
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| 摘 要： | 目前单一的个人信用评估模型发展的很快,而精确性与稳定性却不能同时具备,且第二类误判率的能力弱,本文立足于用线性和非线性方法在个人信用评估中体现的优势,选择具有代表性的logistic回归和径向基函数神经网络方法,通过加权组合对个人信用进行预测评估,提高了评估模型的精确性与稳健性。
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| 关 键 词： | logistic回归 神经网络 组合预测 个人信用 |
| 文章编号： | 1004-292X(2008)02-0008-03 |
| 修稿时间： | 2008年2月21日 |
Personal Credit Scoring Method Based on Weighted Combineing Model |
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| XIE xing-heng,CHEN Yu-fang.Personal Credit Scoring Method Based on Weighted Combineing Model[J].Technoeconomics & Management Research,2008(2):8-10. |
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| Authors: | XIE xing-heng CHEN Yu-fang |
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| Abstract: | With the rapid progress of the personal credit model,the accuracy and stability can not be improved at the same time.Based on the advantages of linear method with non-linear method in the personal credit scoring,chose typical logistic regression and RBF neural network to evaluate the personal credit through weighted combining model,which improve the accuracy and stability of the scoring model. |
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| Keywords: | logistic regression neural network weighted combined forecasting personal credit |
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