On New Concept in Computation of Reduct in Rough Sets Theory

被引：0

作者：

Shaari, Faizah ^{[1
]}

Abu Bakar, Azuraliza ^{[2
]}

Hamdan, Abd Razak ^{[2
]}

机构：

[1] Polytech Sultan Salahuddin Abdul Aziz Shah, Persiaran Usahawan, Seksyen U1, Shah Alam 40150, Selangor De, Malaysia

[2] Univ Natl Malaysia UKM, Ctr Artificial Intelligence Technol, Fac Technol & Infomat Sci, Bangi 43600, Malaysia

来源：

ROUGH SETS AND KNOWLEDGE TECHNOLOGY, PROCEEDINGS | 2009年 / 5589卷

关键词：

NewReduct; non-interesting; redundant; not-important; dispensable; rare;

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：

A new concept of Reduct computation is proposed. This set is referred as NewReduct. It is discovered by defining the Indiscernibility matrix modulo (iDMM D) and Indiscernibility function modulo(iDFM D). Reduct is known as interesting and important set of attributes that able to represent the IS, in adverse the NewReduct is set of superfluous, redundant and non-interesting attributes. The computation of attributes defines sets of dispensable attributes and the partitioning of the objects based on indiscernibility relations shaped the information of a new knowledge. It is assumed that the sets of NewReduct attributes are able to uncover hidden knowledge that lies under a hidden pattern. One important knowledge that may be discovered from the IS or DS is the outliers knowledge.

引用

页码：136 / +

页数：2

共 50 条

[31] Concept Lattices in L-Rough Sets
Chen, Xueyou
ADVANCES IN NEURAL NETWORKS - ISNN 2009, PT 2, PROCEEDINGS, 2009, 5552 : 50 - 59
[32] Concept Approximation Based on Rough Sets and Judgment
Stepaniuk, Jaroslaw
Gora, Grzegorz
Skowron, Andrzej
ROUGH SETS, IJCRS 2019, 2019, 11499 : 16 - 27
[33] Possibility data analysis with rough sets concept
Tanaka, H
Lee, H
Guo, PJ
1998 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AT THE IEEE WORLD CONGRESS ON COMPUTATIONAL INTELLIGENCE - PROCEEDINGS, VOL 1-2, 1998, : 117 - 122
[34] A new computation model for rough set theory based on database systems
Han, JC
Hu, XH
Lin, TY
DATA WAREHOUSING AND KNOWLEDGE DISCOVERY, PROCEEDINGS, 2003, 2737 : 381 - 390
[35] A new rough set-based heuristic algorithm for attribute reduct
Geng, Zhiqiang
Zhu, Qunxiong
WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS, 2006, : 3085 - +
[36] Dynamic Reducts Computation Analysis Based on Rough Sets
Mukamakuza, Carine Pierrette
Wang, Jiayang
Li, Li
2014 10TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION (ICNC), 2014, : 480 - 485
[37] A New Method of Ascertaining Attribute Weight Based on Rough Sets Theory
Bao Xin-zhong
Liu Ying-wen
ECBI: 2009 INTERNATIONAL CONFERENCE ON ELECTRONIC COMMERCE AND BUSINESS INTELLIGENCE, PROCEEDINGS, 2009, : 507 - 510
[38] A New Method for Constructing Decision Tree Based on Rough Sets Theory
Longjun Huang Caiying Zhou Minghe Huang Zhiming Zhuang College of Software Jiangxi Normal University Nanchang China Faculty of Science Jiangxi University of Science and Technology Ganzhou China
南昌工程学院学报, 2006, (02) : 122 - 125
[39] Two new operators in rough set theory with applications to fuzzy sets
Zhang, HG
Liang, HL
Liu, DR
INFORMATION SCIENCES, 2004, 166 (1-4) : 147 - 165
[40] An application of rough sets to graph theory
Chen, Jinkun
Li, Jinjin
INFORMATION SCIENCES, 2012, 201 : 114 - 127

← 1 2 3 4 5 →