DATA MINING USING VARIABLE RANKINGS AND ENHANCED VISUALIZATION METHODS

Dimensional data with attributed categorical variables is mined against a continuous target with any data mining method by ranking variables. The ranked variables are used to generate a tree. A population and a target value, obtained from a top node of the tree, are stored. The top node is removed from the tree to create a new tree with a next top node. Obtaining and storing a next population and a next target value for the next top node, and removing the top node or top field to create a new tree, are repeated. The listing of sequential top node parameters is plotted on a tree cusp curve that provides a graphical user interface enabling identification of a field which affect a greatest or a least number of records, based upon a magnitude of departure of the field from a norm.