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.

Select actionable positive or negative sequential patterns

“…Although there have been some reports of actionable knowledge discovery [8,9,10,16] and selecting actionable patterns/rules or interestingness measures in association rule mining [1,2,4,15,17], none of the previous research considers how to select actionable positive and negative sequential patterns. Very few papers study NSP mining [12,19,20,21,24,26,27], and most primarily focus on how to design a mining algorithm and how to improve the algorithm's efficiency.…”

Action Rules Approach to Solving Diagnostic Problems in Clinical Medicine

“…Action rules, introduced in [5] and investigated further in [6], [7], [8] are constructed from certain pairs of classification rules. Interventions, defined in [8], are conceptually very similar to action rules [10], [11].…”

“…Based on construction methods, action rules discovery can be divided into two types: rulebased and object-based approach. In rule-based approach, actionable patterns [6], [7], [20], [21] are built on the foundations of pre-existing rules. It consists of two main steps: (1) in the first step, a standard learning method is used to detect interesting patterns in the form of classification rules, association rules, or clusters and (2) the second step is to use an automatic or semi-automatic strategy to inspect such results and derive possible action strategies.…”

Speed up gradual rule mining from stream data! A B-Tree and OWA-based approach

“…Gradual rules are very close to action rules firstly introduced by Ras et al in [26] and extended in [34,35] in order to reclassify objects with respect to some distinguished atttribute (called a decision attribute). Intervention [11] or information changes [27] are also comparable to this framework.…”