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Machine learning in bioinformatics /
Machine learning techniques such as Markov models, support vector machines, neural networks, graphical models, etc., have been successful in analyzing life science data because of their capabilities of handling randomness and uncertainties of data and noise and in generalization. This book compiles...
| Clasificación: | Libro Electrónico |
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| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hoboken, N.J. :
Wiley,
©2009.
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| Temas: | |
| Acceso en línea: | Texto completo |
| Sumario: | Machine learning techniques such as Markov models, support vector machines, neural networks, graphical models, etc., have been successful in analyzing life science data because of their capabilities of handling randomness and uncertainties of data and noise and in generalization. This book compiles recent approaches in machine learning, showing promise in addressing different complex bioinformatics applications from prominent researchers in the field. |
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| Descripción Física: | 1 online resource (xviii, 456 pages) : illustrations |
| Bibliografía: | Includes bibliographical references and index. |
| ISBN: | 9780470397428 047039742X 0470397411 9780470397411 |