Structure Learning

Undirected Structure Learning

partial_correlation_threshold
threshold_ug(nodes, ci_tester)	Estimate an undirected graph by testing whether each pair of nodes is independent given all others.

Covariance Structure Learning

covariance_graph_gauss(ci_tester)

Estimate a covariance graph by testing whether each pair of nodes is independent, which reduces to thresholding correlations (after the Fisher z-transform) for multivariate Gaussian data.

DAG Structure Learning

permutation2dag(perm, ci_tester[, verbose, …])	Estimate the minimal IMAP of a DAG which is consistent with the given permutation.
sparsest_permutation(nodes, ci_tester[, …])	Estimate the Markov equivalence class of a DAG using the Sparsest Permutations (SP) algorithm.
gsp(nodes, ci_tester, depth, nruns, verbose, …)	Estimate the Markov equivalence class of a DAG using the Greedy Sparsest Permutations (GSP) algorithm.