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
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
Zusammenfassung
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
Versión del editor
Aparece en las colecciones