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Ensemble methods : foundations and algorithms / Zhi-Hua Zhou.
O'Reilly Online Learning: Academic/Public Library Edition Available online
O'Reilly Online Learning: Academic/Public Library Edition- Format:
- Book
- Author/Creator:
- Zhou, Zhi-Hua, Ph. D.
- Series:
- Chapman & Hall/CRC machine learning & pattern recognition series.
- Chapman & Hall/CRC machine learning & pattern recognition series
- Language:
- English
- Subjects (All):
- Machine learning--Mathematics.
- Algorithms.
- Physical Description:
- 1 online resource (234 p.)
- Edition:
- 1st ed.
- Place of Publication:
- Boca Raton, FL : Taylor & Francis, 2012.
- Language Note:
- English
- Summary:
- 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-- Provided by publisher.
- Contents:
- Front Cover; Preface; Notations; Contents; 1. Introduction; 2. Boosting; 3. Bagging; 4. Combination Methods; 5. Diversity; 6. Ensemble Pruning; 7. Clustering Ensembles; 8. Advanced Topics; References
- Notes:
- A Chapman & Hall book.
- Includes bibliographical references and index.
- Description based on metadata supplied by the publisher and other sources.
- ISBN:
- 9781040070512
- 1040070515
- 9780429151095
- 0429151098
- 9781439830055
- 1439830053
- OCLC:
- 798535723
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