Learning Bayesian Networks with Incomplete Data by Augmentation
Learning Bayesian Networks with Incomplete Data by Augmentation
We present new algorithms for learning Bayesian networks from data with missing values using a data augmentation approach. An exact Bayesian network learning algorithm is obtained by recasting the problem into a standard Bayesian network learning problem without missing data. As expected, the exact algorithm does not scale to large …