A Comparison of Rule Sets Generated from Databases by Indiscernibility Relation - A Rough Sets Approach

Author

Brtka, Vladimir ; Berkovic, Ivana ; Stokic, Edith ; Srdic, Biljana

Author_Institution

Tech. Fac., Zrenjanin

fYear

2007

fDate

6-8 Sept. 2007

Firstpage

279

Lastpage

282

Abstract

Rough sets theory (Pawlak 1980s) proved to be an excellent mathematical tool for the task of automated extraction of If-Then rule sets from table-organized data. In this paper, we employ an approach based on the relation of indiscernibility and rough sets theory in comparison to the method based on pure classification. We have used a well-known ROSETTA software system. The main goal of this work is to compare rule set generated by ROSETTA and rule set generated by method based on pure classification. Comparison is conducted on real-life database from domain of medicine including recently discovered protein hormone Leptin.

Keywords

database management systems; knowledge acquisition; knowledge representation; pattern classification; rough set theory; If-Then rule sets; Leptin; ROSETTA software system; automated extraction; databases; indiscernibility relation; knowledge representation; mathematical tool; medicine domain; protein hormone; pure classification; rough sets theory; rule generation; table-organized data; Anatomy; Biochemistry; Data analysis; Data mining; Databases; Diseases; Endocrine system; Proteins; Rough sets; Software systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Computer Communication and Processing, 2007 IEEE International Conference on

Conference_Location

Cluj-Napoca

Print_ISBN

978-1-4244-1491-8

Type

conf

DOI

10.1109/ICCP.2007.4352177

Filename

4352177