Ensemble methods foundations and algorithms
This comprehensive book presents an in-depth and systematic introduction to ensemble methods for researchers in machine learning, data mining, and related areas. It helps readers solve modem problems in machine learning using these methods. The author covers the spectrum of research in ensemble meth...
| Autor principal: | |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Boca Raton, FL :
Taylor & Francis
2012.
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| Edición: | 1st ed |
| Colección: | Chapman & Hall/CRC machine learning & pattern recognition series.
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009755216806719 |
| Sumario: | This comprehensive book presents an in-depth and systematic introduction to ensemble methods for researchers in machine learning, data mining, and related areas. It helps readers solve modem problems in machine learning using these methods. The author covers the spectrum of research in ensemble methods, including such famous methods as boosting, bagging, and rainforest, along with current directions and methods not sufficiently addressed in other books. Chapters explore cutting-edge topics, such as semi-supervised ensembles, cluster ensembles, and comprehensibility, as well as successful applications-- |
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| Notas: | A Chapman & Hall book. |
| Descripción Física: | 1 online resource (234 p.) |
| Bibliografía: | Includes bibliographical references and index. |
| ISBN: | 9780429151095 9781439830055 |
