1. A method of displaying feature importance in predictive modeling comprising the steps of: calling a regression engine on a set of training data that outputs importance measures for explanatory variables for predicting a target variable; calling a graphical model structural learning module that outputs a graph on the explanatory variables and representing a correlation structure among said explanatory variables; and 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.