2026-06-01T03:18:14Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/99432025-01-17T01:05:29Zcom_10259_4219com_10259_5086com_10259_2604col_10259_4220

Garrido Labrador, José Luis 745 600 0000-0002-3441-4223 Maudes Raedo, Jesús M. 352 600 0000-0001-8808-412X Rodríguez Diez, Juan José 477 600 0000-0002-3291-2739 García Osorio, César 212 600 0000-0002-1206-1084 2025-01-16T11:19:52Z 2025-01-16T11:19:52Z 2025-01 2352-7110 http://hdl.handle.net/10259/9943 10.1016/j.softx.2024.102024 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. This work was supported through the Junta de Castilla 𝑦� León (JCyL) (regional government) under project BU055P20 (JCyL/FEDER, UE), the Spanish Ministry of Science and Innovation under project PID2020- 119894GB-I00 co-financed through European Union FEDER funds, and project TED2021-129485B-C43 funded by MCIN/AEI/ 10.13039/501 100011033 and the European Union NextGenerationEU/PRTR. J.L. Garrido-Labrador is supported through Consejería de Educación of the Junta de Castilla 𝑦� León and the European Social Fund through a pre-doctoral grant EDU/875/2021 (Spain). application/pdf eng Elsevier SoftwareX. 2025, V. 29, p. 102024 https://doi.org/10.1016/j.softx.2024.102024 Atribución 4.0 Internacional http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess Semi-supervised learning Python library Self-training Co-training Restricted set classification Informática Educación Computer science Education SSLearn: A Semi-Supervised Learning library for Python info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion SoftwareX 29 102024 THUMBNAIL Garrido-sx_2025.pdf.jpg Garrido-sx_2025.pdf.jpg IM Thumbnail image/jpeg 4841 https://riubu.ubu.es/bitstream/10259/9943/4/Garrido-sx_2025.pdf.jpg d5260de694c73a78afe4654ce2945471 MD5 4 LICENSE license.txt license.txt text/plain; charset=utf-8 999 https://riubu.ubu.es/bitstream/10259/9943/3/license.txt b295bcbce42e2caabeb0c623d3860c06 MD5 3 CC-LICENSE license_rdf license_rdf application/rdf+xml; charset=utf-8 908 https://riubu.ubu.es/bitstream/10259/9943/2/license_rdf 0175ea4a2d4caec4bbcc37e300941108 MD5 2 ORIGINAL Garrido-sx_2025.pdf Garrido-sx_2025.pdf application/pdf 895609 https://riubu.ubu.es/bitstream/10259/9943/1/Garrido-sx_2025.pdf dfdf5035a9c4d4e259a016ec7d4cd19d MD5 1 10259/9943 oai:riubu.ubu.es:10259/9943 2025-01-17 02:05:29.188 Repositorio Institucional de la Universidad de Burgos bubrep@ubu.es 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