Constructing Nominal X-of-N Attributes

Most constructive induction researchers focus only on new boolean attributes This paper reports a new constructive induction algor i thm, called XofN, that constructs new nominal attributes in the form of X-of-N representations An X-of-N is a Bet containing one or more attribute-value pairs For a given instance, its value corresponds to the number of its at tribute-value pairs that are true The promising preliminary experimental results, on both artificial and real-world domains, show that constructing new nominal attributes in the form of X-of-N representations can significantly improve the performance of selective induction in terms of both higher prediction accuracy and lower theory complexity