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    Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10259/9943

    Título
    SSLearn: A Semi-Supervised Learning library for Python
    Autor
    Garrido Labrador, José LuisUBU authority Orcid
    Maudes Raedo, Jesús M.UBU authority Orcid
    Rodríguez Diez, Juan JoséUBU authority Orcid
    García Osorio, CésarUBU authority Orcid
    Publicado en
    SoftwareX. 2025, V. 29, p. 102024
    Editorial
    Elsevier
    Fecha de publicación
    2025-01
    ISSN
    2352-7110
    DOI
    10.1016/j.softx.2024.102024
    Abstract
    SSLearn is an open-source Python-based library that advances semi-supervised learning (SSL) with a focus on wrapper algorithms and restricted set classification (RSC), a novel paradigm. It fosters innovation by allowing researchers to modify methods or create new ones, facilitating access to state-of-the-art algorithms and comparative studies. As the only library incorporating RSC for constrained classification, SSLearn fills an important gap in SSL tools. Fully compatible with Scikit-Learn, it integrates seamlessly into research workflows, lowering the barrier to entry to SSL and catalyzing its adoption in diverse domains. This makes SSLearn a critical resource for advancing SSL research and applications.
    Palabras clave
    Semi-supervised learning
    Python library
    Self-training
    Co-training
    Restricted set classification
    Materia
    Informática
    Computer science
    Educación
    Education
    URI
    http://hdl.handle.net/10259/9943
    Versión del editor
    https://doi.org/10.1016/j.softx.2024.102024
    Collections
    • Artículos ADMIRABLE
    Atribución 4.0 Internacional
    Documento(s) sujeto(s) a una licencia Creative Commons Atribución 4.0 Internacional
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    Garrido-sx_2025.pdf
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