توضیحات
ABSTRACT
Subgroup discovery is a data mining task half-way between descriptive and predictive data mining. Nowadays it is very relevant for researches due to the fact that the knowledge extracted is simple and interesting. For this task, evolutionary fuzzy systems are well suited algorithms because they can find a good trade-off between multiple objectives in large search spaces. In fact, this paper presents the SDEFSR package, which contains all evolutionary fuzzy systems for subgroup discovery presented throughout the literature. It is a package without dependencies on other software, providing functions with recommended default parameters. In addition, it brings a graphical user interface to avoid the user having to know all the algorithm’s parameters.
INTRODUCTION
Subgroup discovery (SD) is a data mining field that aims to describe data using supervised learning techniques. The goal is to find simple, general and interesting patterns with respect to a given variable of interest. Throughout the literature, SD has been applied with success to different real-world problems in areas such as marketing [del Jesus et al.(2007), Berlanga et al.(2006)], medicine
[Carmona et al.(2015), Carmona et al.(2013), Stiglic and Kokol(2012), Gamberger et al.(2003)]ande-learning [Poitras et al.(2016), Lemmerich et al.(2011), Carmona et al.(2010b)], amongst others
[Atzmueller et al.(2016), Jin et al.(2014), Rodriguez et al.(2013), Carmona et al.(2012)]. SD is a rule learning process within a complex search space. Therefore, the search strategy used becomes a key factor in the efficiency of the method. Different strategies can be found in the literature such as
beam search in the algorithm CN2-SD [Lavrač et al.(2004b)] and Apriori-SD [Kavšek and Lavrač(2006)],
exhaustive algorithms such as SDMap [Atzmueller and Puppe(2006)] or Evolutionary Algorithms (EAs),
for example.
Year : 2016
Publisher : R Journal
By : Ángel M. García, Francisco Charte, Pedro González, Cristóbal J. Carmona and María J. del Jesus
File Information : English Language / 21 Page /Size : 276 K
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سال : 2016
ناشر : R Journal
کاری از : Ángel M. García, Francisco Charte, Pedro González, Cristóbal J. Carmona and María J. del Jesus
اطلاعات فایل : زبان انگلیسی / 21 صفحه / حجم : 276 K
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