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Bayesian Inference with Missing Data
数据缺失条件下的贝叶斯推断方法

Keywords: 数据缺失,贝叶斯推断方法,概率,数据挖掘,机器学习

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Abstract:

Recently Bayesian network(BN) becomus a noticeable research direction in Data Mining.In this paper we introduce missing data mechanisms firstly,and then some methods to do Baysesian inference with missing data based on these missing data mechanisms.All of these must be useful in practice especially when data is scare and expensive.It can foresee that Bayesian networks will become a powerful tool in Data Mining with all of these methods above offered.

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