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Título: | Genetic prediction in bovine meat production : Is worth integrating bayesian and machine learning approaches? A comprenhensive analysis |
Autor: | Fariello, Maria Ines Armstrong, Eileen Fernández, Alicia |
Tipo: | Ponencia |
Palabras clave: | Parametric, Non parametric, Genomic, Selection, Prediction, Fusion |
Descriptores: | Procesamiento de Señales |
Fecha de publicación: | 2015 |
Resumen: | Genomic prediction is a still growing field, as good predictions can have important economic impact in both, agronomics and health. In this article, we make a brief review and a comprehensive analysis of classical predictors used in the area. We propose a strategy to choose and ensemble of methods and to combine their results, to take advantage of the complementarity that some predictors have. |
Editorial: | Springer International Publishing |
EN: | 20th Iberoamerican Congress, CIARP 2015, Montevideo, Uruguay, 9-12 nov, 2015 |
Citación: | Fariello, M.I., Amstrong, E., Fernandez, A. "Genetic prediction in bovine meat production: is worth integrating bayesian and machine learning approaches? A comprenhensive analysis" Pardo, A., Kittler, J. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2015. Lecture Notes in Computer Science, vol 9423. Springer, Cham. https://doi.org/10.1007/978-3-319-25751-8_2 |
Departamento académico: | Procesamiento de Señales |
Grupo de investigación: | Tratamiento de Imágenes |
Aparece en las colecciones: | Publicaciones académicas y científicas - Instituto de Ingeniería Eléctrica |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | ||
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FAF15.pdf | 227,07 kB | Adobe PDF | Visualizar/Abrir |
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