Ensemble methods : foundations and algorithms /

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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...

Ausführliche Beschreibung

Gespeichert in:
1. Verfasser:
Zhou, Zhi-Hua, Ph. D.
Format:
Elektronisch E-Book
Sprache:
Englisch
Veröffentlicht:
Boca Raton, FL : Taylor & Francis, 2012.
Ausgabe:
1st ed.
Zusammenfassung:
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--
Umfang:
1 online resource (234 p.)
Anmerkungen:
A Chapman & Hall book.
Anmerkungen:
English
Bibliografie:
Includes bibliographical references and index.
ISBN:
9781040070512
1040070515
9780429151095
0429151098
9781439830055
1439830053
Schlagworte:
Machine learning > Mathematics.
Algorithms.
Bezugswerke:
Links: