Bayesian network structure learning (via constraint-based, score-based
and hybrid algorithms), parameter learning (via ML and Bayesian
estimators) and inference.

This package implements the Grow-Shrink (GS) algorithm, the
Incremental Association (IAMB) algorithm, the Interleaved-IAMB
(Inter-IAMB) algorithm, the Fast-IAMB (Fast-IAMB) algorithm, the
Max-Min Parents and Children (MMPC) algorithm, the Hiton-PC algorithm,
the ARACNE and Chow-Liu algorithms, the Hill-Climbing (HC) greedy
search algorithm, the Tabu Search (TABU) algorithm, the Max-Min
Hill-Climbing (MMHC) algorithm and the two-stage Restricted
Maximization (RSMAX2) algorithm for both discrete and Gaussian
networks, along with many score functions and conditional independence
tests. The Naive Bayes and the Tree-Augmented Naive Bayes (TAN)
classifiers are also implemented.

Some utility functions (model comparison and manipulation, random
data generation, arc orientation testing, simple and advanced plots)
are included, as well as support for parameter estimation and
inference, conditional probability queries and cross-validation.
