7. The system for displaying feature importance in predictive modeling recited in claim 6 , wherein the feature importance measure, output by the regression engine, for each node in the graph, is displayed by the display as an attribute selected from color, size, and texture.
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.