IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i10p1425-d1389677.html
   My bibliography  Save this article

Eigenvalue Distributions in Random Confusion Matrices: Applications to Machine Learning Evaluation

Author

Listed:
  • Oyebayo Ridwan Olaniran

    (Department of Statistics, Faculty of Physical Sciences, University of Ilorin, llorin 1515, Nigeria)

  • Ali Rashash R. Alzahrani

    (Mathematics Department, Faculty of Sciences, Umm Al-Qura University, Makkah 24382, Saudi Arabia)

  • Mohammed R. Alzahrani

    (Department of Psychology, Faculty of Education, Umm Al-Qura University, Al-Abidiyah, Makkah 24382, Saudi Arabia)

Abstract

This paper examines the distribution of eigenvalues for a 2 × 2 random confusion matrix used in machine learning evaluation. We also analyze the distributions of the matrix’s trace and the difference between the traces of random confusion matrices. Furthermore, we demonstrate how these distributions can be applied to calculate the superiority probability of machine learning models. By way of example, we use the superiority probability to compare the accuracy of four disease outcomes machine learning prediction tasks.

Suggested Citation

  • Oyebayo Ridwan Olaniran & Ali Rashash R. Alzahrani & Mohammed R. Alzahrani, 2024. "Eigenvalue Distributions in Random Confusion Matrices: Applications to Machine Learning Evaluation," Mathematics, MDPI, vol. 12(10), pages 1-14, May.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:10:p:1425-:d:1389677
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/10/1425/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/12/10/1425/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Peyrache, Antonio & Rose, Christiern & Sicilia, Gabriela, 2020. "Variable selection in Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 282(2), pages 644-659.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Oyebayo Ridwan Olaniran & Aliu Omotayo Sikiru & Jeza Allohibi & Abdulmajeed Atiah Alharbi & Nada MohammedSaeed Alharbi, 2025. "Hybrid Random Feature Selection and Recurrent Neural Network for Diabetes Prediction," Mathematics, MDPI, vol. 13(4), pages 1-25, February.

    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. Antonio Peyrache, 2024. "A Homothetic and Additively Separable Production Frontier," CEPA Working Papers Series WP012024, School of Economics, University of Queensland, Australia.
    2. Gao, Qiuming & Wang, Derek, 2021. "Hospital efficiency and equity in health care delivery: A study based in China," Socio-Economic Planning Sciences, Elsevier, vol. 76(C).
    3. Imad Bou-Hamad & Abdel Latef Anouze & Ibrahim H. Osman, 2022. "A cognitive analytics management framework to select input and output variables for data envelopment analysis modeling of performance efficiency of banks using random forest and entropy of information," Annals of Operations Research, Springer, vol. 308(1), pages 63-92, January.
    4. Qingwei Shi & Hong Ren & Weiguang Cai & Jingxin Gao, 2020. "How to Set the Proper CO 2 Reduction Targets for the Provincial Building Sector of China?," Sustainability, MDPI, vol. 12(24), pages 1-22, December.
    5. Anna Łozowicka & Bartłomiej Lach, 2022. "CI-DEA: A Way to Improve the Discriminatory Power of DEA—Using the Example of the Efficiency Assessment of the Digitalization in the Life of the Generation 50+," Sustainability, MDPI, vol. 14(6), pages 1-22, March.
    6. Raul Moragues & Juan Aparicio & Miriam Esteve, 2023. "Ranking the Importance of Variables in a Nonparametric Frontier Analysis Using Unsupervised Machine Learning Techniques," Mathematics, MDPI, vol. 11(11), pages 1-24, June.
    7. Zohaib Zahid & Jijian Zhang & Chongyan Gao & Judit Oláh, 2025. "ICT-Driven Strategies for Enhancing Energy Efficiency in G20 Economies: Moderating the Role of Governance in Achieving Environmental Sustainability," Energies, MDPI, vol. 18(3), pages 1-22, February.
    8. Bielov, Constantine & Mitomo, Hitoshi & Hämmäinen, Heikki, 2022. "Efficiency frontier of OECD MNOs: Multinational vs Domestic," Telecommunications Policy, Elsevier, vol. 46(5).
    9. Toloo, Mehdi & Tone, Kaoru & Izadikhah, Mohammad, 2023. "Selecting slacks-based data envelopment analysis models," European Journal of Operational Research, Elsevier, vol. 308(3), pages 1302-1318.
    10. Qiang Deng, 2024. "A Combined OCBA–AIC Method for Stochastic Variable Selection in Data Envelopment Analysis," Mathematics, MDPI, vol. 12(18), pages 1-15, September.
    11. Sila Mishra, 2023. "‘Cyclic syndrome’ of arrears and efficiency of Indian judiciary," SN Business & Economics, Springer, vol. 3(1), pages 1-27, January.
    12. Wasi Ul Hassan Shah & Yuting Lu & Gang Hao & Hong Yan & Rizwana Yasmeen, 2022. "Impact of “Three Red Lines” Water Policy (2011) on Water Usage Efficiency, Production Technology Heterogeneity, and Determinant of Water Productivity Change in China," IJERPH, MDPI, vol. 19(24), pages 1-23, December.

    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:2024:i:10:p:1425-:d:1389677. 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.