Universal attribute reduction problem

Mikhail Ju Moshkov; Marcin Piliszczuk; Beata Zielosko

doi:10.1007/978-3-540-69029-0_6

Universal attribute reduction problem

Mikhail Ju Moshkov, Marcin Piliszczuk, Beata Zielosko

Research output: Contribution to journal › Article › peer-review

Abstract

The attribute reduction problem (it is required to find a reduct with minimal or close to minimal cardinality) is one of the main problems of rough set theory and related theories such as test theory and LAD. There are different variants of the notion of reduct: reducts for information systems, usual decision and local reducts for decision tables, decision and local reducts which are based on the generalized decision, etc. Interesting discussion of various kinds of reducts can be found in [38]. © 2008 Springer-Verlag Berlin Heidelberg.

Original language	English (US)
Journal	Studies in Computational Intelligence
Volume	145
DOIs	https://doi.org/10.1007/978-3-540-69029-0_6
State	Published - Sep 18 2008
Externally published	Yes

ASJC Scopus subject areas

Artificial Intelligence

Access to Document

10.1007/978-3-540-69029-0_6

Cite this

@article{b5473e6104054d9e9ff97d013e636b43,

title = "Universal attribute reduction problem",

abstract = "The attribute reduction problem (it is required to find a reduct with minimal or close to minimal cardinality) is one of the main problems of rough set theory and related theories such as test theory and LAD. There are different variants of the notion of reduct: reducts for information systems, usual decision and local reducts for decision tables, decision and local reducts which are based on the generalized decision, etc. Interesting discussion of various kinds of reducts can be found in [38]. {\textcopyright} 2008 Springer-Verlag Berlin Heidelberg.",

author = "Moshkov, {Mikhail Ju} and Marcin Piliszczuk and Beata Zielosko",

note = "Generated from Scopus record by KAUST IRTS on 2023-09-21",

year = "2008",

month = sep,

day = "18",

doi = "10.1007/978-3-540-69029-0_6",

language = "English (US)",

volume = "145",

journal = "Studies in Computational Intelligence",

issn = "1860-949X",

publisher = "Springer Verlag",

}

TY - JOUR

T1 - Universal attribute reduction problem

AU - Moshkov, Mikhail Ju

AU - Piliszczuk, Marcin

AU - Zielosko, Beata

N1 - Generated from Scopus record by KAUST IRTS on 2023-09-21

PY - 2008/9/18

Y1 - 2008/9/18

N2 - The attribute reduction problem (it is required to find a reduct with minimal or close to minimal cardinality) is one of the main problems of rough set theory and related theories such as test theory and LAD. There are different variants of the notion of reduct: reducts for information systems, usual decision and local reducts for decision tables, decision and local reducts which are based on the generalized decision, etc. Interesting discussion of various kinds of reducts can be found in [38]. © 2008 Springer-Verlag Berlin Heidelberg.

AB - The attribute reduction problem (it is required to find a reduct with minimal or close to minimal cardinality) is one of the main problems of rough set theory and related theories such as test theory and LAD. There are different variants of the notion of reduct: reducts for information systems, usual decision and local reducts for decision tables, decision and local reducts which are based on the generalized decision, etc. Interesting discussion of various kinds of reducts can be found in [38]. © 2008 Springer-Verlag Berlin Heidelberg.

UR - http://link.springer.com/10.1007/978-3-540-69029-0_6

UR - http://www.scopus.com/inward/record.url?scp=51649105695&partnerID=8YFLogxK

U2 - 10.1007/978-3-540-69029-0_6

DO - 10.1007/978-3-540-69029-0_6

M3 - Article

SN - 1860-949X

VL - 145

JO - Studies in Computational Intelligence

JF - Studies in Computational Intelligence

ER -

Universal attribute reduction problem

Abstract

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this