Data-driven constructive induction in AQ17-PRE: A method and experiments

Abstract

A method is presented for constructive induction, in which new attributes are constructed as various functions of original attributes. Such a method is called data-driven constructive induction, because new attributes are derived from an analysis of the data (examples) rather than the generated rules. Attribute construction and rule generation are repeated until a termination condition, such as the satisfaction of a rule quality measure, is met. The first step of this method, the generation of new attributes, has been implemented in AQ17-PRE. Initial experiments with AQ17-PRE have shown that it leads to an improvement of the learned rules in terms of both their simplicity and their accuracy on testing examples.<>