1. A computerized method for generating a decision-tree classifier from a training set of records, each record having: (i) at least one attribute, each attribute having an attribute value, (ii) a class label of the class to which the record belongs, and (iii) a record ID, and wherein a decision tree includes a root node, a plurality of interior nodes, and a plurality of leaf nodes, all of the records initially belonging to the root node, the method comprising the steps of: generating an attribute list for each attribute of the records, each entry in the attribute list having the attribute value, the class label, and the record ID of the record from which the attribute value is obtained; sorting attribute lists for numeric attributes based on attribute values; and creating the decision tree by repeatedly reading and partitioning the records at each node using the attribute lists until each leaf node of the decision tree contains records from only one class; wherein said partitioning step requires only a single read for each non-root node.