Rough sets theory and its extensions for attribute reduction: a review
The rough sets theory is a mathematical tool to express vagueness by means of boundary region of a set. The main advantage of this implementation of vagueness is that it requires no human input or domain knowledge other than the given data set. Several efforts have been made to make close the rough...
Saved in:
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
REA Press
2021-06-01
|
| Series: | Big Data and Computing Visions |
| Subjects: | |
| Online Access: | https://www.bidacv.com/article_142085_eb1f70ca734778c2b84efe1859a862d9.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832579330852519936 |
|---|---|
| author | Sadegh Eskandari |
| author_facet | Sadegh Eskandari |
| author_sort | Sadegh Eskandari |
| collection | DOAJ |
| description | The rough sets theory is a mathematical tool to express vagueness by means of boundary region of a set. The main advantage of this implementation of vagueness is that it requires no human input or domain knowledge other than the given data set. Several efforts have been made to make close the rough sets theory and machine learning tasks. In this regard several extensions and modifications of the original theory are proposed. This paper provides the basic concepts of the theory as well as its well-known extensions and modifications. |
| format | Article |
| id | doaj-art-59438c0886c54ac79969bdd10d50bc95 |
| institution | Kabale University |
| issn | 2783-4956 2821-014X |
| language | English |
| publishDate | 2021-06-01 |
| publisher | REA Press |
| record_format | Article |
| series | Big Data and Computing Visions |
| spelling | doaj-art-59438c0886c54ac79969bdd10d50bc952025-01-30T12:21:15ZengREA PressBig Data and Computing Visions2783-49562821-014X2021-06-01129610010.22105/bdcv.2021.142085142085Rough sets theory and its extensions for attribute reduction: a reviewSadegh Eskandari0Department of Computer Science, University of Guilan, Rasht, Iran.The rough sets theory is a mathematical tool to express vagueness by means of boundary region of a set. The main advantage of this implementation of vagueness is that it requires no human input or domain knowledge other than the given data set. Several efforts have been made to make close the rough sets theory and machine learning tasks. In this regard several extensions and modifications of the original theory are proposed. This paper provides the basic concepts of the theory as well as its well-known extensions and modifications.https://www.bidacv.com/article_142085_eb1f70ca734778c2b84efe1859a862d9.pdfrough set theorydata sciencedata set |
| spellingShingle | Sadegh Eskandari Rough sets theory and its extensions for attribute reduction: a review Big Data and Computing Visions rough set theory data science data set |
| title | Rough sets theory and its extensions for attribute reduction: a review |
| title_full | Rough sets theory and its extensions for attribute reduction: a review |
| title_fullStr | Rough sets theory and its extensions for attribute reduction: a review |
| title_full_unstemmed | Rough sets theory and its extensions for attribute reduction: a review |
| title_short | Rough sets theory and its extensions for attribute reduction: a review |
| title_sort | rough sets theory and its extensions for attribute reduction a review |
| topic | rough set theory data science data set |
| url | https://www.bidacv.com/article_142085_eb1f70ca734778c2b84efe1859a862d9.pdf |
| work_keys_str_mv | AT sadegheskandari roughsetstheoryanditsextensionsforattributereductionareview |