Transformational machine learning: Learning how to learn from many related scientific problems

Almost all machine learning (ML) is based on representing examples using intrinsic features. When there are multiple related ML problems (tasks), it is possible to transform these features into extrinsic features by first training ML models on other tasks and letting them each make predictions for e...

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Detalles Bibliográficos
Autores principales: Olier, Ivan, Orhobor, Oghenejokpeme I., Dash, Tirtharaj, Davis, Andy M., Soldatova, Larisa N., Vanschoren, Joaquin, King, Ross D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2021
Materias:
Physical Sciences
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8670494/
https://www.ncbi.nlm.nih.gov/pubmed/34845013
http://dx.doi.org/10.1073/pnas.2108013118

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8670494/
https://www.ncbi.nlm.nih.gov/pubmed/34845013
http://dx.doi.org/10.1073/pnas.2108013118

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