An overview of emerging pattern mining in supervised descriptive rule discovery: taxonomy, empirical study, trends, and prospects

Abstract

Emerging pattern mining is a data mining task that aims to discover discriminative patterns, which can describe emerging behavior with respect to a property of interest. In recent years, the description of datasets has become an interesting field due to the easy acquisition of knowledge by the experts. In this review, we will focus on the descriptive point of view of the task. We collect the existing approaches that have been proposed in the literature and group them together in a taxonomy in order to obtain a general vision of the task. A complete empirical study demonstrates the suitability of the approaches presented. This review also presents future trends and emerging prospects within pattern mining and the benefits of knowledge extracted from emerging patterns.

Study on the use of different quality measures within a multi-objective evolutionary algorithm approach for emerging pattern mining in big data environments

“…EPM is a data mining task for searching patterns whose support significantly differs between two classes or databases [7,8]. A pattern is considered as emerging if and only if its growth rate (GR) is larger than a given threshold ρ > 1.…”

“…These can be classified according to the approach used to mine the emerging patterns (EPs). A complete review of these approaches can be found in [8]. Nevertheless, the majority of the algorithms developed along the literature has been focused on classification purposes.…”

“…In addition, these rules should be easily comprehensible and interesting for the expert. These characteristics allow us to define several objectives that the rule models extracted in EPM should have [8,18]:…”

“…Following the results presented in [20], where a set of quality measures were analysed in order to determine their correlation, the results of the study showed that the analysed quality measures present a low average correlation amongst them. According to this study, and the studies presented in [8,18] the most interesting quality measures for EPM are depicted below:…”

“…The emerging pattern mining (EPM) [7,8] is a data mining task within the supervised descriptive rule discovery (SDRD) framework [9] whose main aim is the description of discriminative characteristics, i.e., the values of the variables in data, amongst classes of a dataset or the description of emerging phenomena in data that arrives continuously to the system. The knowledge extracted is usually represented by means of rules.…”