Rough set theory

Walczak, B. and Massart, D.L. (1999) Rough sets theory. Chemom. Intdl. Lab. Syst., 47, 1—16. 

Vol. 174. Ajith Abraham, Rafael Falc6n and Rafael Bello (Eds.) Rough Set Theory A True Landmark in Data Analysis, 2009 ISBN 978-3-540-89886-3... 

Cao Xiu-Ying, Liang Jing-Guo, 2002. The Method of Ascertaining Attribute Weight Based on Rough Sets Theory. Chinese Journal of Management Science, 10(5) 9-10. 

Sun Bin, Wang Li-Jie, 2006. Study of the Method for Determining Weight Based on Rough Set Theory. Computer Engineering and Applications, 29 216-217. 

A ROUGH SET THEORY APPROACH TO THE ANALYSIS OF GENE EXPRESSION PROFILES... 

Rough set theory (RST), first introduced by Pawlak more than 20 years ago [6], is a set-based method that is well suited for dealing with a wide variety of discrete data that can be represented by DTs [7-11]. RST appears to be well suited to the problem at hand since, as will be seen in the sequel, it provides computationally tractable procedures for identifying minimal subsets of attributes, that is, genes, in this work [12,13]. These subsets of attributes maintain key relationships in the data that support the generation of simple linguistic rules. This procedure is similar in many ways to dimensionality reduction techniques that are routinely employed to continuous variables to reduce the size and complexity of mathematical models [14]. 

Rough set theory differs from most other rule-based methods, especially those associated with artificial intelligence methods. In such methods, rules (typically called production rules ) that encapsulate knowledge are input into the system and... 

Rough set theory appears to be an ideal method for dealing with gene expression data such as that reported on here (see e.g., [12,13]). However, the methodology has a broader range of applicability for characterizing biological systems and subsystems [45 7]. 

QianY, Liang J, Dang C. Converse approximation and rule extraction from decision tables in rough set theory. Comput Mathematics 2008 55 1754—1765. 

Krysihski J, Skrzypczak A, Demski G, et al. Application of rough set theory in structure-activity relationships of anti-electrostatic Imidazolium compounds. Quant Struct-Act Relat2002 20 395 01. 

Walczak B, Massart DL. Tutorial rough sets theory. Chemomet Intell Lab Syst 1999 47 1-16. 

Krysinski J. Application of rough sets theory to the analysis of structure-activity -relationships of anti-microbial pyridinium compounds. Pharmazie 1995 50 593-597. 

Petit J, Maggiora GM. Application of rough set theory to structure-activity relationships. 229th National American Chemical Society Meeting 2005 Mar 13-17 San Diego. Division of Chemical Information Abstr. No. 51... 

Koyama M, Hasegawa K, Arakawa M, et al. Application of rough set theory to high throughput screening data for rational selection of lead compounds. Chem-Bio Inf J 2008 8 85-95. 

Medina-Franco JL, Maggiora GM, Goodwin JT, et al. Rule-based analysis of ADMET data using rough set theory. 232nd National American Chemical Society Meeting 2006 Sept 10-14 San Francisco. Division of Computers in Chemistry, Abstr. No. 140. 

Bai Ch., Sarkis J., 2010, Green Supplier Development Analytical Evaluation Using Rough Set Theory, Journal of Cleaner Production, 18(12), pp. 1200-1210. 

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