A Gaussian mixed model for learning discrete Bayesian networks

作者：Balov Nikolay^*

来源：Statistics & Probability Letters, 2011, 81(2): 220-230.

DOI：10.1016/j.spl.2010.11.009

• Bayesian networks
• Learning
• Mixture models
• MLE
• EM algorithm

In this paper, we address the problem of learning discrete Bayesian networks from noisy data. A graphical model based on a mixture of Gaussian distributions with categorical mixing structure coming from a discrete Bayesian network is considered. The network learning is formulated as a maximum likelihood estimation problem and performed by employing an EM algorithm. The proposed approach is relevant to a variety of statistical problems for which Bayesian network models are suitable from simple regression analysis to learning gene/protein regulatory networks from microarray data.

• 出版日期2011-2