# Structure Learning

The HUGIN Graphical User Interface provides the user with powerful structure learning capabilities (i.e., learning the structure of a Bayesian-network model from data (a set of cases)). Structure learning can be performed via the Learning Wizard (which allows data to be read from data files, to be preprocessed, etc.) or by activating one of the structure learning algorithms directly.

A number of algorithms are available for structure learning: The PC algorithm, the NPC algorithm, the Greedy search-and-score algorithm, the Chow-Liu tree algorithm, the Rebane-Pearl polytree algoritm, the Tree Augmented Naive Bayes algorithm or the Hierarchical Naive Bayes algorithm. See the also Structure Learning Tutorial for more information.