Local Generalized Multigranulation Variable Precision Tolerance Rough Sets and its Attribute Reduction

In the era of big data, as for an important granular computing model, rough set model is an important tool for us to deal with data. As a kind of extension of classical rough sets, multigranulation rough sets have two forms, including optimistic and pessimistic cases. However, these two models have...

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Autores principales:	Yueli Zhou, Guoping Lin
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Tolerance relation local rough sets attribute reduction set-valued information systems Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/efa71720834c488a9d975a6d7a9079fb
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spelling	oai:doaj.org-article:efa71720834c488a9d975a6d7a9079fb2021-11-18T00:10:21ZLocal Generalized Multigranulation Variable Precision Tolerance Rough Sets and its Attribute Reduction2169-353610.1109/ACCESS.2021.3124339https://doaj.org/article/efa71720834c488a9d975a6d7a9079fb2021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9594816/https://doaj.org/toc/2169-3536In the era of big data, as for an important granular computing model, rough set model is an important tool for us to deal with data. As a kind of extension of classical rough sets, multigranulation rough sets have two forms, including optimistic and pessimistic cases. However, these two models have their shortcomings, one is too loose, and the other is too strict. To overcome the above shortcomings, based on the concept of local multigranulation tolerance rough sets in set-valued information systems, the local generalized multigranulation variable precision tolerance rough sets model by introducing characteristic function is established. Then the related properties are studied and proved. In addition, we define the concepts of lower approximate quality, inner and outer importance of attribute according to different granularity structures in set-valued decision information systems because different granularity structures have different effectives on the decision classes. Finally, the local attribute reduction algorithm and the global attribute reduction algorithm of local generalized multigranulation variable precision tolerance rough sets in set-valued decision information systems are given, and the effectiveness of the algorithms is proved by using UCI data sets.Yueli ZhouGuoping LinIEEEarticleTolerance relationlocal rough setsattribute reductionset-valued information systemsElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 147237-147249 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Tolerance relation local rough sets attribute reduction set-valued information systems Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Tolerance relation local rough sets attribute reduction set-valued information systems Electrical engineering. Electronics. Nuclear engineering TK1-9971 Yueli Zhou Guoping Lin Local Generalized Multigranulation Variable Precision Tolerance Rough Sets and its Attribute Reduction
description	In the era of big data, as for an important granular computing model, rough set model is an important tool for us to deal with data. As a kind of extension of classical rough sets, multigranulation rough sets have two forms, including optimistic and pessimistic cases. However, these two models have their shortcomings, one is too loose, and the other is too strict. To overcome the above shortcomings, based on the concept of local multigranulation tolerance rough sets in set-valued information systems, the local generalized multigranulation variable precision tolerance rough sets model by introducing characteristic function is established. Then the related properties are studied and proved. In addition, we define the concepts of lower approximate quality, inner and outer importance of attribute according to different granularity structures in set-valued decision information systems because different granularity structures have different effectives on the decision classes. Finally, the local attribute reduction algorithm and the global attribute reduction algorithm of local generalized multigranulation variable precision tolerance rough sets in set-valued decision information systems are given, and the effectiveness of the algorithms is proved by using UCI data sets.
format	article
author	Yueli Zhou Guoping Lin
author_facet	Yueli Zhou Guoping Lin
author_sort	Yueli Zhou
title	Local Generalized Multigranulation Variable Precision Tolerance Rough Sets and its Attribute Reduction
title_short	Local Generalized Multigranulation Variable Precision Tolerance Rough Sets and its Attribute Reduction
title_full	Local Generalized Multigranulation Variable Precision Tolerance Rough Sets and its Attribute Reduction
title_fullStr	Local Generalized Multigranulation Variable Precision Tolerance Rough Sets and its Attribute Reduction
title_full_unstemmed	Local Generalized Multigranulation Variable Precision Tolerance Rough Sets and its Attribute Reduction
title_sort	local generalized multigranulation variable precision tolerance rough sets and its attribute reduction
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/efa71720834c488a9d975a6d7a9079fb
work_keys_str_mv	AT yuelizhou localgeneralizedmultigranulationvariableprecisiontoleranceroughsetsanditsattributereduction AT guopinglin localgeneralizedmultigranulationvariableprecisiontoleranceroughsetsanditsattributereduction
_version_	1718425259010424832

Local Generalized Multigranulation Variable Precision Tolerance Rough Sets and its Attribute Reduction

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