Imbalanced learning foundations, algorithms, and applications
Solving imbalanced learning problems is critical in numerous data-intensive networked systems, including surveillance, security, Internet, finance, biomedical, and defense, to name a few. The first comprehensive look at this new branch of machine learning, this volume offers a critical review of the...
| Otros Autores: | , |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Hoboken, NJ :
Wiley
c2013.
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009665113706719 |
| Sumario: | Solving imbalanced learning problems is critical in numerous data-intensive networked systems, including surveillance, security, Internet, finance, biomedical, and defense, to name a few. The first comprehensive look at this new branch of machine learning, this volume offers a critical review of the problem of imbalanced learning, covering the state-of-the-art in techniques, principles, and real-world applications. Scientists and engineers will learn how to tackle the problem of learning from imbalanced datasets, and gain insight into current developments in the field as well as future research.--[Source inconnue] |
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| Notas: | Description based upon print version of record. |
| Descripción Física: | 1 online resource (224 p.) Also available in print |
| Bibliografía: | Includes bibliographical references and index. |
| ISBN: | 9781118646335 9781118646205 |
