Naive Bayes method in operational risk level prediction

Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (12): 26-28.

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Naive Bayes method in operational risk level prediction

WANG Shuang-cheng^1,2,LENG Cui-ping¹,HOU Cai-hong¹

1.Department of Information Science，Shanghai Lixin University of Commerce，Shanghai 201620，China
2.Risk Management Research Institute，Shanghai Lixin University of Commerce，Shanghai 201620，China

Received:2007-12-05 Revised:2008-01-24 Online:2008-04-21 Published:2008-04-21
Contact: WANG Shuang-cheng

操作风险等级预测的朴素贝叶斯方法研究

王双成^1,2,冷翠平¹,侯彩虹¹

1.上海立信会计学院信息科学系，上海 201620
2.上海立信会计学院中国立信风险管理研究院，上海 201620

通讯作者: 王双成

Abstract

Abstract: It is difficult to accumulate a large number of data with high quality in operational risk.Naive Bayes classifier is the one of best classifiers used to small data set classification.It is suitable for operational risk level prediction.In this paper，firstly，the process of learning and classing is presented on naive Bayes classifier with complete data sets.Then，a method naive Bayes classifier learning with missing data is developed based on star structure and Gibbs sampling.The existing problems can be avoided in local optimization，information losing and redundancy.

Key words: operational risk, level prediction, naive Bayes classifier, missing data, Gibbs sampling

摘要： 操作风险数据积累比较困难，而且往往不完整，朴素贝叶斯分类器是目前进行小样本分类最优秀的分类器之一，适合于操作风险等级预测。在对具有完整数据朴素贝叶斯分类器学习和分类的基础上，提出了基于星形结构和Gibbs sampling的具有丢失数据朴素贝叶斯分类器学习方法，能够避免目前常用的处理丢失数据方法所带来的局部最优、信息丢失和冗余等方面的问题。

关键词: 操作风险, 等级预测, 朴素贝叶斯分类器, 丢失数据, Gibbs抽样

WANG Shuang-cheng^1,2,LENG Cui-ping¹,HOU Cai-hong¹. Naive Bayes method in operational risk level prediction[J]. Computer Engineering and Applications, 2008, 44(12): 26-28.

王双成^1,2,冷翠平¹,侯彩虹¹. 操作风险等级预测的朴素贝叶斯方法研究[J]. 计算机工程与应用, 2008, 44(12): 26-28.

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Naive Bayes method in operational risk level prediction

操作风险等级预测的朴素贝叶斯方法研究

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