Ensemble methods
Subtitle: foundations and algorithms
By: Zhi-Hua Zhou
Series: Chapman & Hall/CRC machine learning & pattern recognition series
Publisher: Taylor & Francis
Published: 2012
Place of publication: Boca Raton, FL
Language: eng
Number of pages: 222
ISBN-13: 9781439830031
Subjects: COMPUTERS / Machine Theory; COMPUTERS / Database Management / Data Mining; BUSINESS & ECONOMICS / Statistics; Set theory; Multiple comparisons (Statistics); Mathematical analysis
Description: "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"--
Notes: Includes bibliographical references and index.