Action rules mining

Abstract

Action rules assume that attributes in a database are divided into two groups: stable and flexible. In general, an action rule can be constructed from two rules extracted earlier from the same database. Furthermore, we assume that these two rules describe two different decision classes and our goal is to reclassify objects from one of these classes into the other one. Flexible attributes are essential in achieving that goal because they provide a tool for making hints to a user about what changes within some values of flexible attributes are needed for a given group of objects to reclassify them into a new decision class. A new subclass of attributes called semi-stable attributes is introduced. Semi-stable attributes are typically a function of time and undergo deterministic changes (e.g., attribute age or height). So, the set of conditional attributes is partitioned into stable, semi-stable, and flexible. Depending on the semantics of attributes, some semi-stable attributes can be treated as flexible and the same new action rules can be constructed. These new action rules are usually built to replace some existing action rules whose confidence is too low to be of any interest to a user. The confidence of new action rules is always higher than the confidence of rules they replace. Additionally, the notion of the cost and feasibility of an action rule is introduced in this article. A heuristic strategy for constructing feasible action rules that have high confidence and possibly the lowest cost is proposed. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 719–736, 2005.