The briefest reduct of rough sets based on genetic algorithm

Author

Hong-bo Guan ; Bao-an Yang

Author_Institution

Glorious Sun Sch. of Bus. & Manage., Shanghai

fYear

2008

fDate

12-14 Dec. 2008

Firstpage

23

Lastpage

27

Abstract

This paper focuses on the discussion about the briefest reduct of Rough Sets which is extracted by genetic algorithm. The fitting function is designed by the combination of the relying degree of RS and sum of seeds which is the attributes of data. Genetic Algorithm operator is applied and the algorithm is tested by UCI database. After the analysis and discussion, RGA and RGA_2 have been proved available. In the discussion, crossover and mutation probability have got a experienced number. Increasing the sum of seeds, and saving the last generation optimized seeds can be improving the efficiency of algorithm.

Keywords

data reduction; genetic algorithms; mathematical operators; probability; rough set theory; UCI database; briefest reduction; data reduction; genetic algorithm; mutation probability; rough set theory; Algorithm design and analysis; Biological cells; Data mining; Databases; Genetic algorithms; Genetic mutations; Oceans; Rough sets; Set theory; Sun;

fLanguage

English

Publisher

ieee

Conference_Titel

IT in Medicine and Education, 2008. ITME 2008. IEEE International Symposium on

Conference_Location

Xiamen

Print_ISBN

978-1-4244-3616-3

Electronic_ISBN

978-1-4244-2511-2

Type

conf

DOI

10.1109/ITME.2008.4743816

Filename

4743816