10. The system for displaying feature importance in predictive modeling recited in claim 6 , wherein the graphical model is obtained by calling an estimation method for dependency trees.
6. A system for displaying feature importance in predictive modeling comprising: a regression engine operable on a set of training data that performs predictive modeling on the set of training data and outputs importance measures for explanatory variables for predicting a target variable; a graphical model structural learning module that receives the importance measures output by the regression engine, computes correlational information among the explanatory variables, and outputs a graph on the explanatory variables and represents a feature correlation structure among said explanatory variables; and a display for displaying a feature importance measure, output by the regression engine, for each node in the graph, as an attribute of a node in the graph output by the graphical model structural learning module, to combine the predictive modeling of the regression engine with the feature correlation among the explanatory variables.