Patent ID: 7801924

Claim:
A computer-implemented method of constructing a decision tree generating a prediction for a predicted attribute of a transaction, the method comprising: mining a plurality of frequent predictive itemsets from a training dataset, the plurality of frequent predictive itemsets comprising values for one or more predictor attributes; storing the plurality of frequent predictive itemsets in a hierarchical frequent predictive itemset tree data structure, wherein child nodes of the hierarchical frequent predictive itemset tree data structure represent one of the plurality of frequent predictive itemsets that is a superset of an immediate parent node of the respective child node; determining best attribute splits for respective of the plurality of frequent predictive itemsets; and constructing the decision tree, wherein the constructing comprises generating nodes for inclusion in the decision tree based on the plurality of frequent predictive itemsets according to the best attribute splits for the plurality of frequent predictive itemsets, the generating comprising: choosing nodes of one or more best attribute split paths of the hierarchical frequent predictive itemset tree data structure; and for the chosen nodes, generating corresponding decision nodes in the decision tree, the generated decision nodes associated with one of the one or more predictor attributes; and whereby respective of the decision nodes of a path of the decision tree consisting of one or more of the nodes corresponding to one or more of the chosen nodes is associated with a predictor attribute that is different from the one or more predictor attributes associated with other decision nodes in the path.