Coordinate-Descent Algorithm for Learning Sparse Discrete Bayesian Networks

Structure learning of Bayesian network using coordinate-descent algorithm. This algorithm is designed for discrete network assuming a multinomial data set, and we use a multi-logit model to do the regression. The algorithm is described in Gu, Fu and Zhou (2016) .

discretecdAlgorithm

An algorithm to learn structure of discrete Bayesian network, this package can deal with observational data, interventional data, or a mixture of both.

algorithm

• cd.run is the main function to run coordinate descent algorithm. With the adaptive option, users may choose to use regular group lasso penalty, or adaptive group lasso penalty.
• max_lambda is a function to calculate the maximum value of lambda that will penalized all edges to zero.