IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2023i1p90-d1308130.html
   My bibliography  Save this article

An Algorithm for Computing All Rough Set Constructs for Dimensionality Reduction

Author

Listed:
  • Yanir González-Díaz

    (Department of Computer Science, Instituto Nacional de Astrofísica, Óptica y Electrónica (INAOE), Puebla 72840, Mexico)

  • José Fco. Martínez-Trinidad

    (Department of Computer Science, Instituto Nacional de Astrofísica, Óptica y Electrónica (INAOE), Puebla 72840, Mexico
    These authors contributed equally to this work.)

  • Jesús A. Carrasco-Ochoa

    (Department of Computer Science, Instituto Nacional de Astrofísica, Óptica y Electrónica (INAOE), Puebla 72840, Mexico
    These authors contributed equally to this work.)

  • Manuel S. Lazo-Cortés

    (Graduate Division, Tecnológico Nacional de México/IT Tlalnepantla, Tlalnepantla de Baz 54070, Mexico
    These authors contributed equally to this work.)

Abstract

In rough set theory, a construct is an attribute subset with the same ability to discern objects belonging to different classes as the whole set of attributes, while maintaining the similarity between objects belonging to the same class. Although algorithms for reducts computation can be adapted to compute constructs, practical problems exist where these algorithms cannot compute all constructs within a reasonable time frame. Therefore, this paper introduces an algorithm for computing all constructs of a decision system. The results of experiments with various decision systems (both artificial and real-world) suggest that our algorithm is, in most cases, faster than the state-of-the-art algorithms when the simplified binary discernibility–similarity matrix has a density of less than 0.29.

Suggested Citation

  • Yanir González-Díaz & José Fco. Martínez-Trinidad & Jesús A. Carrasco-Ochoa & Manuel S. Lazo-Cortés, 2023. "An Algorithm for Computing All Rough Set Constructs for Dimensionality Reduction," Mathematics, MDPI, vol. 12(1), pages 1-19, December.
  • Handle: RePEc:gam:jmathe:v:12:y:2023:i:1:p:90-:d:1308130
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/1/90/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/12/1/90/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Greco, Salvatore & Matarazzo, Benedetto & Slowinski, Roman, 2001. "Rough sets theory for multicriteria decision analysis," European Journal of Operational Research, Elsevier, vol. 129(1), pages 1-47, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Eduardo Fernández & José Rui Figueira & Jorge Navarro, 2023. "A theoretical look at ordinal classification methods based on comparing actions with limiting boundaries between adjacent classes," Annals of Operations Research, Springer, vol. 325(2), pages 819-843, June.
    2. Doumpos, M. & Marinakis, Y. & Marinaki, M. & Zopounidis, C., 2009. "An evolutionary approach to construction of outranking models for multicriteria classification: The case of the ELECTRE TRI method," European Journal of Operational Research, Elsevier, vol. 199(2), pages 496-505, December.
    3. Bouyssou, Denis & Marchant, Thierry, 2007. "An axiomatic approach to noncompensatory sorting methods in MCDM, II: More than two categories," European Journal of Operational Research, Elsevier, vol. 178(1), pages 246-276, April.
    4. Fernandez, Eduardo & Navarro, Jorge & Bernal, Sergio, 2010. "Handling multicriteria preferences in cluster analysis," European Journal of Operational Research, Elsevier, vol. 202(3), pages 819-827, May.
    5. Pawel Lezanski & Maria Pilacinska, 2018. "The dominance-based rough set approach to cylindrical plunge grinding process diagnosis," Journal of Intelligent Manufacturing, Springer, vol. 29(5), pages 989-1004, June.
    6. Choudhary, Devendra & Shankar, Ravi, 2012. "An STEEP-fuzzy AHP-TOPSIS framework for evaluation and selection of thermal power plant location: A case study from India," Energy, Elsevier, vol. 42(1), pages 510-521.
    7. García Cáceres, Rafael Guillermo & Aráoz Durand, Julián Arturo & Gómez, Fernando Palacios, 2009. "Integral analysis method - IAM," European Journal of Operational Research, Elsevier, vol. 192(3), pages 891-903, February.
    8. Azam, Nouman & Zhang, Yan & Yao, JingTao, 2017. "Evaluation functions and decision conditions of three-way decisions with game-theoretic rough sets," European Journal of Operational Research, Elsevier, vol. 261(2), pages 704-714.
    9. Kadziński, Miłosz & Wójcik, Michał & Ciomek, Krzysztof, 2022. "Review and experimental comparison of ranking and choice procedures for constructing a univocal recommendation in a preference disaggregation setting," Omega, Elsevier, vol. 113(C).
    10. Hu, Qiwei & Chakhar, Salem & Siraj, Sajid & Labib, Ashraf, 2017. "Spare parts classification in industrial manufacturing using the dominance-based rough set approach," European Journal of Operational Research, Elsevier, vol. 262(3), pages 1136-1163.
    11. Leung, Yee & Fischer, Manfred M. & Wu, Wei-Zhi & Mi, Ju-Sheng, 2008. "A rough set approach for the discovery of classification rules in interval-valued information systems," MPRA Paper 77767, University Library of Munich, Germany.
    12. Deparis, Stéphane & Mousseau, Vincent & Öztürk, Meltem & Huron, Caroline, 2015. "The effect of bi-criteria conflict on matching-elicited preferences," European Journal of Operational Research, Elsevier, vol. 242(3), pages 951-959.
    13. Pegdwendé Minoungou & Vincent Mousseau & Wassila Ouerdane & Paolo Scotton, 2023. "A MIP-based approach to learn MR-Sort models with single-peaked preferences," Annals of Operations Research, Springer, vol. 325(2), pages 795-817, June.
    14. Salvatore Barbagallo & Simona Consoli & Nello Pappalardo & Salvatore Greco & Santo Zimbone, 2006. "Discovering Reservoir Operating Rules by a Rough Set Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(1), pages 19-36, February.
    15. Oppio, Alessandra & Dell’Ovo, Marta & Torrieri, Francesca & Miebs, Grzegorz & Kadziński, Miłosz, 2020. "Understanding the drivers of Urban Development Agreements with the rough set approach and robust decision rules," Land Use Policy, Elsevier, vol. 96(C).
    16. Alessandro Scuderi & Luisa Sturiale & Giuseppe Timpanaro & Agata Matarazzo & Silvia Zingale & Paolo Guarnaccia, 2022. "A Model to Support Sustainable Resource Management in the “Etna River Valleys” Biosphere Reserve: The Dominance-Based Rough Set Approach," Sustainability, MDPI, vol. 14(9), pages 1-19, April.
    17. Zopounidis, Constantin & Doumpos, Michael, 2002. "Multicriteria classification and sorting methods: A literature review," European Journal of Operational Research, Elsevier, vol. 138(2), pages 229-246, April.
    18. Wu, Zhibin & Huang, Shuai & Xu, Jiuping, 2019. "Multi-stage optimization models for individual consistency and group consensus with preference relations," European Journal of Operational Research, Elsevier, vol. 275(1), pages 182-194.
    19. Jonas Damidavičius & Marija Burinskienė & Jurgita Antuchevičienė, 2020. "Assessing Sustainable Mobility Measures Applying Multicriteria Decision Making Methods," Sustainability, MDPI, vol. 12(15), pages 1-15, July.
    20. Liu, Jiapeng & Liao, Xiuwu & Kadziński, Miłosz & Słowiński, Roman, 2019. "Preference disaggregation within the regularization framework for sorting problems with multiple potentially non-monotonic criteria," European Journal of Operational Research, Elsevier, vol. 276(3), pages 1071-1089.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:12:y:2023:i:1:p:90-:d:1308130. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.