Non-deterministic Information in Rough Sets: A Survey and Perspective

被引：0

作者：

Sakai, Hiroshi ^{[1
]}

Wu, Mao ^{[2
]}

Yamaguchi, Naoto ^{[2
]}

Nakata, Michinori ^{[3
]}

机构：

[1] Kyushu Inst Technol, Fac Engn, Dept Basic Sci, Kitakyushu, Fukuoka 8048550, Japan

[2] Kyushu Inst Technol, Grad Sch Engn, Kitakyushu, Fukuoka 8048550, Japan

[3] Josai Int Univ, Fac Management & Informat Sci, Chiba 2830002, Japan

来源：

ROUGH SETS AND KNOWLEDGE TECHNOLOGY: 8TH INTERNATIONAL CONFERENCE | 2013年 / 8171卷

关键词：

Rough sets; Non-deterministic information; Incomplete information; Survey; Information dilution; Privacy-preserving; RULES; APPROXIMATIONS; ALGORITHM;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We have been coping with issues connected with non-deterministic information in rough sets. Non-deterministic information is a kind of incomplete information, and it defines a set in which the actual value exists, but we do not know which is the actual value. If the defined set is equal to the domain of attribute values, we may see this is corresponding to a missing value. We need to pick up the merits in each information, and need to apply them to analyzing data sets. In this paper, we describe our opinion on non-deterministic information as well as incomplete information, some algorithms, software tools, and its perspective in rough sets.

引用

页码：7 / 15

页数：9

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