Attribute reduction in variable precision rough set model

被引：32
|
作者：
Inuiguchi, Masahiro [1 ]
机构：
[1] Osaka Univ, Grad Sch Engn Sci, Dept Syst Innovat, Osaka 5608531, Japan
来源：
INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS | 2006年 / 14卷 / 04期
关键词：
variable precision rough set; reduct; discernability matrix; Boolean function;
D O I：
10.1142/S0218488506004126
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, attribute reduction in variable precision rough set model is discussed. Several kinds of reducts preserving some of lower approximations, upper approximations, boundary regions and the unpredictable region are discussed. Relations among those kinds of reducts are investigated. As a basis for reduct computation, Boolean function representations of the preservation of lower approximations, upper approximations, boundary regions and the unpredictable region are discussed. Throughout this paper, the great difference between the analysis using variable precision rough sets and the classical rough set analysis is emphasized.
引用
收藏
页码：461 / 479
页数：19
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