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[null,"1.","Record Nr.",null,"UNINA9910462400503321"]
[null,null,"Autore",null,"Zhou Zhi-Hua, Ph. D."]
[null,null,"Titolo",null,"Ensemble methods : foundations and algorithms / / Zhi-Hua Zhou"]
[null,null,"Pubbl/distr/stampa",null,"Boca Raton, Fla. : , : CRC Press, , 2012"]
[null,null,"ISBN",null,"0-429-15109-8"]
[{"$nulls":4},"1-4398-3005-3"]
[null,null,"Descrizione fisica",null,"1 online resource (234 p.)"]
[null,null,"Collana",null,"Chapman & Hall/CRC machine learning & pattern recognition series"]
[null,null,"Disciplina",null,"006.3/1"]
[null,null,"Soggetti",null,"Multiple comparisons (Statistics)"]
[{"$nulls":4},"Set theory"]
[{"$nulls":4},"Mathematical analysis"]
[{"$nulls":4},"Electronic books."]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","A Chapman & Hall book."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"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"]
[null,null,null,"Sommario/riassunto","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--"]