Finding reducts with user specified criteria

Author

Shao, J.

Author_Institution

Dept. of Comput. Sci., Univ. of Wales, Cardiff, UK

fYear

1997

Firstpage

352

Lastpage

357

Abstract

Rough set theory is emerging as a powerful tool for inducing classification knowledge from databases. Central to this technique is the problem of searching for a reduct, which is a minimal subset of information that has the same ability to classify data as when the full set of information is used. In this paper, we introduce a method for finding reducts based on two user-specified criteria. This is in contrast to many existing techniques which use user-independent criteria for measuring information redundancy. Our approach allows flexibility in knowledge extraction and is capable of dealing with different levels of noise in data for different applications

Keywords

database theory; deductive databases; knowledge acquisition; noise; pattern classification; redundancy; set theory; classification knowledge induction; data noise levels; databases; flexibility; information redundancy; knowledge discovery; knowledge extraction; minimal information subset; reduct searching; rough set theory; user-specified criteria; Active noise reduction; Computer science; Data mining; Electronic mail; Noise level; Noise measurement; Redundancy; Rough sets; Signal to noise ratio; Spatial databases;

fLanguage

English

Publisher

ieee

Conference_Titel

Database and Expert Systems Applications, 1997. Proceedings., Eighth International Workshop on

Conference_Location

Toulouse

Print_ISBN

0-8186-8147-0

Type

conf

DOI

10.1109/DEXA.1997.617309

Filename

617309