On Variable Precision Generalized Rough Sets and Incomplete Decision Tables

Yu Ru Syau; Churn Jung Liau; En Bing Lin

doi:10.3233/FI-2021-2014

On Variable Precision Generalized Rough Sets and Incomplete Decision Tables

Yu Ru Syau, Churn Jung Liau, En Bing Lin

Mathematics

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

We present variable precision generalized rough set approach to characterize incomplete decision tables. We show how to determine the discernibility threshold for a reflexive relational decision system in the variable precision generalized rough set model. We also point out some properties of positive regions and prove a statement of the necessary condition for weak consistency of an incomplete decision table. We present two examples to illustrate the results obtained in this paper.

Original language	English
Pages (from-to)	75-92
Number of pages	18
Journal	Fundamenta Informaticae
Volume	179
Issue number	1
DOIs	https://doi.org/10.3233/FI-2021-2014
State	Published - 2021

Keywords

Rough sets
consistency
incomplete decision tables
relative discernibility
variable precision rough set models

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10.3233/FI-2021-2014

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abstract = "We present variable precision generalized rough set approach to characterize incomplete decision tables. We show how to determine the discernibility threshold for a reflexive relational decision system in the variable precision generalized rough set model. We also point out some properties of positive regions and prove a statement of the necessary condition for weak consistency of an incomplete decision table. We present two examples to illustrate the results obtained in this paper.",

keywords = "Rough sets, consistency, incomplete decision tables, relative discernibility, variable precision rough set models",

author = "Syau, {Yu Ru} and Liau, {Churn Jung} and Lin, {En Bing}",

note = "Funding Information: This work was partially supported by a grant from the Ministry of Science and Technology (TAIWAN) No. MOST 107-2221-E-150-027. The authors appreciate anonymous reviewers{\textquoteright} valuable comments. Publisher Copyright: {\textcopyright} 2021 - IOS Press. All rights reserved.",

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AU - Liau, Churn Jung

AU - Lin, En Bing

N1 - Funding Information: This work was partially supported by a grant from the Ministry of Science and Technology (TAIWAN) No. MOST 107-2221-E-150-027. The authors appreciate anonymous reviewers’ valuable comments. Publisher Copyright: © 2021 - IOS Press. All rights reserved.

PY - 2021

Y1 - 2021

N2 - We present variable precision generalized rough set approach to characterize incomplete decision tables. We show how to determine the discernibility threshold for a reflexive relational decision system in the variable precision generalized rough set model. We also point out some properties of positive regions and prove a statement of the necessary condition for weak consistency of an incomplete decision table. We present two examples to illustrate the results obtained in this paper.

AB - We present variable precision generalized rough set approach to characterize incomplete decision tables. We show how to determine the discernibility threshold for a reflexive relational decision system in the variable precision generalized rough set model. We also point out some properties of positive regions and prove a statement of the necessary condition for weak consistency of an incomplete decision table. We present two examples to illustrate the results obtained in this paper.

KW - Rough sets

KW - consistency

KW - incomplete decision tables

KW - relative discernibility

KW - variable precision rough set models

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DO - 10.3233/FI-2021-2014

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JO - Fundamenta Informaticae

JF - Fundamenta Informaticae

IS - 1

ER -

On Variable Precision Generalized Rough Sets and Incomplete Decision Tables

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Keywords

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