Data science and predictive analytics biomedical and health applications using R
| Otros Autores: | |
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| Formato: | Libro |
| Idioma: | Inglés |
| Publicado: |
Cham, Switzerland :
Springer
[2023]
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| Edición: | Second edition |
| Colección: | The Springer Series in Applied Machine Learning,
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| Materias: | |
| Ver en Universidad de Deusto: | https://oceano.biblioteca.deusto.es/primo-explore/search?query=any,contains,991006803071403351&tab=default_tab&search_scope=deusto_alma&vid=deusto |
Solicitar por préstamo interbibliotecario:
Correo
| Notas: | "The book's fourteen chapters start with an introduction and progressively build the foundational skills from visualization to linear modeling, dimensionality reduction, supervised classification, black-box machine learning techniques, qualitative learning methods, unsupervised clustering, model performance assessment, feature selection strategies, longitudinal data analytics, optimization, neural networks, and deep learning, Individual modules and complete end-to-end pipeline protocols are avialable as functional R electronic markdown notebooks. These workflows support an active learning platform for comprehensive data manipulation, sophisticated analytics, interactive visualization, and effective dissemination of open problems, current knowledge, scientific tools, and research findings"--Cubierta posterior. Índice. |
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| Descripción Física: | XXXIV, 918 páginas : ilustraciones, gráficos (color) ; 24 cm |
| ISBN: | 9783031174827 |
