Description
Coordinate-Descent Algorithm for Learning Sparse Discrete Bayesian Networks.
Description
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) <arXiv:1403.2310>.
README.md
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 theadaptive
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.