دورية أكاديمية
Ensemble methods and semi-supervised learning for information fusion: A review and future research directions
| العنوان: | Ensemble methods and semi-supervised learning for information fusion: A review and future research directions |
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| المؤلفون: | Garrido Labrador, José Luis, Serrano Mamolar, Ana, Maudes Raedo, Jesús M., Rodríguez Diez, Juan José, García Osorio, César |
| بيانات النشر: | Elsevier |
| سنة النشر: | 2024 |
| المجموعة: | Repositorio Institucional de la Universidad de Burgos (RIUBU) |
| مصطلحات موضوعية: | Semi-supervised learning, Ensemble learning, Information fusion, Semi-supervised ensemble classification, Label scarcity, Bibliographic review, Research trends, Experimental protocols, Informática, Computer science |
| الوصف: | Advances over the past decade at the intersection of information fusion methods and Semi-Supervised Learning (SSL) are investigated in this paper that grapple with challenges related to limited labelled data. To do so, a bibliographic review of papers published since 2013 is presented, in which ensemble methods are combined with new machine learning algorithms. A total of 128 new proposals using SSL algorithms for ensemble construction are identified and classified. All the methods are categorised by approach, ensemble type, and base classifier. Experimental protocols, pre-processing, dataset usage, unlabelled ratios, and statistical tests are also assessed, underlining the major trends, and some shortcomings of particular studies. It is evident from this literature review that foundational algorithms such as self-training and co-training are influencing current developments, and that innovative ensemble techniques are continuing to emerge. Additionally, valuable guidelines are identified in the review for improving research into intrinsically semi-supervised and unsupervised pre-processing methods, especially for regression tasks. ; This work was supported through the Junta de Castilla y León (JCyL) (regional goverment) 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/10.13039/501100011033 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). |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | application/pdf |
| اللغة: | English |
| تدمد: | 1566-2535 |
| العلاقة: | Information Fusion. 2024, V. 107, 102310; https://doi.org/10.1016/j.inffus.2024.102310Test; info:eu-repo/grantAgreement/Junta de Castilla y León//BU055P20//Métodos y Aplicaciones Industriales del Aprendizaje Semisupervisado/; info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-119894GB-I00/ES/APRENDIZAJE AUTOMATICO CON DATOS ESCASAMENTE ETIQUETADOS PARA LA INDUSTRIA 4.0/; info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica, Técnica y de Innovación 2021-2023/TED2021-129485B-C43/ES/Sistemas dinámicos inteligentes centrados en el usuario para la Prevención de Riesgos Laborales/; http://hdl.handle.net/10259/8872Test |
| DOI: | 10.1016/j.inffus.2024.102310 |
| الإتاحة: | https://doi.org/10.1016/j.inffus.2024.102310Test http://hdl.handle.net/10259/8872Test |
| حقوق: | Attribution-NonCommercial-NoDerivatives 4.0 Internacional ; http://creativecommons.org/licenses/by-nc-nd/4.0Test/ ; info:eu-repo/semantics/openAccess |
| رقم الانضمام: | edsbas.E31E195B |
| قاعدة البيانات: | BASE |
| تدمد: | 15662535 |
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| DOI: | 10.1016/j.inffus.2024.102310 |