Rough Sets and Rule Induction in Imperfect Information Systems

Do VanNguyen; Koichi Yamada; Muneyuki Unehara

doi:10.5120/15495-4286

Rough Sets and Rule Induction in Imperfect Information Systems

International Journal of Computer Applications ◽

10.5120/15495-4286 ◽

2014 ◽

Vol 89 (5) ◽

pp. 1-8 ◽

Cited By ~ 2

Author(s):

Do VanNguyen ◽

Koichi Yamada ◽

Muneyuki Unehara

Keyword(s):

Information Systems ◽

Rough Sets ◽

Imperfect Information ◽

Rule Induction

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Rough Sets and Rule Induction from Indiscernibility Relations Based on Possible World Semantics in Incomplete Information Systems with Continuous Domains

Studies in Big Data - Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges ◽

10.1007/978-3-030-59338-4_1 ◽

2020 ◽

pp. 3-23

Author(s):

Michinori Nakata ◽

Hiroshi Sakai ◽

Keitarou Hara

Keyword(s):

Information Systems ◽

Incomplete Information ◽

Rough Sets ◽

Rule Induction ◽

Possible World ◽

Possible World Semantics ◽

Continuous Domains ◽

Incomplete Information Systems

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α-Dominance relation and rough sets in interval-valued information systems

Information Sciences ◽

10.1016/j.ins.2014.10.003 ◽

2015 ◽

Vol 294 ◽

pp. 334-347 ◽

Cited By ~ 46

Author(s):

Xibei Yang ◽

Yong Qi ◽

Dong-Jun Yu ◽

Hualong Yu ◽

Jingyu Yang

Keyword(s):

Information Systems ◽

Rough Sets ◽

Dominance Relation ◽

Interval Valued

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Rule induction based on rough sets from information tables having continuous domains

CAAI Transactions on Intelligence Technology ◽

10.1049/trit.2019.0025 ◽

2019 ◽

Vol 4 (4) ◽

pp. 237-244 ◽

Cited By ~ 2

Author(s):

Michinori Nakata ◽

Hiroshi Sakai ◽

Keitarou Hara

Keyword(s):

Rough Sets ◽

Rule Induction ◽

Continuous Domains ◽

Information Tables

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Rule Induction Based on Indiscernible Classes from Rough Sets in Information Tables with Continuous Values

Rough Sets - Lecture Notes in Computer Science ◽

10.1007/978-3-319-99368-3_25 ◽

2018 ◽

pp. 323-336 ◽

Cited By ~ 3

Author(s):

Michinori Nakata ◽

Hiroshi Sakai ◽

Keitarou Hara

Keyword(s):

Rough Sets ◽

Rule Induction ◽

Information Tables

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A Concept of Multi Rough Sets Defined on Multi-contextual Information Systems

Proceedings of Second International Conference on Electrical Systems, Technology and Information 2015 (ICESTI 2015) - Lecture Notes in Electrical Engineering ◽

10.1007/978-981-287-988-2_3 ◽

2016 ◽

pp. 31-44

Author(s):

Rolly Intan

Keyword(s):

Information Systems ◽

Rough Sets ◽

Contextual Information

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Rough Sets Based Incremental Rule Acquisition in Set-Valued Information Systems

Autonomous Systems: Developments and Trends - Studies in Computational Intelligence ◽

10.1007/978-3-642-24806-1_11 ◽

2012 ◽

pp. 135-146

Author(s):

Junbo Zhang ◽

Tianrui Li ◽

Da Ruan

Keyword(s):

Information Systems ◽

Rough Sets ◽

Rule Acquisition

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Soft dominance based rough sets with applications in information systems

International Journal of Approximate Reasoning ◽

10.1016/j.ijar.2019.06.009 ◽

2019 ◽

Vol 113 ◽

pp. 171-195 ◽

Cited By ~ 2

Author(s):

Abbas Ali ◽

Muhammad Irfan Ali ◽

Noor Rehman

Keyword(s):

Information Systems ◽

Rough Sets

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Soft Computing for Evolutionary Information Systems — Potentials of Rough Sets

Soft Computing in Industrial Applications ◽

10.1007/978-1-4471-0509-1_42 ◽

2000 ◽

pp. 481-494 ◽

Cited By ~ 1

Author(s):

A. B. Patki ◽

G. V. Raghunathan ◽

Soumik Ghosh ◽

S. Sivasubramanian ◽

Azar Khurshid

Keyword(s):

Information Systems ◽

Soft Computing ◽

Rough Sets ◽

Evolutionary Information

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Reduction of Neighborhood-Based Generalized Rough Sets

Journal of Applied Mathematics ◽

10.1155/2011/409181 ◽

2011 ◽

Vol 2011 ◽

pp. 1-22 ◽

Cited By ~ 3

Author(s):

Zhaohao Wang ◽

Lan Shu ◽

Xiuyong Ding

Keyword(s):

Information Systems ◽

Set Theory ◽

Rough Set ◽

Rough Sets ◽

Rough Set Theory ◽

Open Problems ◽

The Third ◽

Generalized Rough Sets

Rough set theory is a powerful tool for dealing with uncertainty, granularity, and incompleteness of knowledge in information systems. This paper discusses five types of existing neighborhood-based generalized rough sets. The concepts of minimal neighborhood description and maximal neighborhood description of an element are defined, and by means of the two concepts, the properties and structures of the third and the fourth types of neighborhood-based rough sets are deeply explored. Furthermore, we systematically study the covering reduction of the third and the fourth types of neighborhood-based rough sets in terms of the two concepts. Finally, two open problems proposed by Yun et al. (2011) are solved.

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