000			02181nam a2200373Ia 4500
001			CAH0KE11360PDF
003			BD-DhSAU
005			20151012144310.0
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007			cr||||
008			120720s2012 fluad sb 001 0 eng d
020			_a9781439830055 (ebook : PDF)
040			_aBD-DhSAU _cBD-DhSAU
090			_aQA278.4 _b.Z47 2012
092			_a006.31 _bZ638
100	1		_aZhou, Zhi-Hua, _cPh. D.
245	1	0	_aEnsemble methods _h[electronic resource] : _bfoundations and algorithms / _cZhi-Hua Zhou.
260			_aBoca Raton, Fla. : _bCRC Press, _c2012.
300			_axiv, 222 p. : _bill.
490	1		_aChapman & Hall/CRC machine learning & pattern recognition series
500			_a"A Chapman & Hall book."
504			_aIncludes bibliographical references (p. 187-218) and index.
505	0		_a1. Introduction -- 2. Boosting -- 3. Bagging -- 4. Combination methods -- 5. Diversity -- 6. Ensemble pruning -- 7. Clustering ensembles -- 8. Advanced topics.
520			_a"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"-- _cProvided by publisher.
530			_aAlso available in print edition.
538			_aMode of access: World Wide Web.
650		0	_aMultiple comparisons (Statistics)
650		0	_aSet theory.
650		0	_aMathematical analysis.
655		7	_aElectronic books. _2lcsh
776	1		_z9781439830031 (hardback)
830		0	_aChapman & Hall/CRC machine learning & pattern recognition series.
856	4	0	_uhttp://marc.crcnetbase.com/isbn/9781439830055 _qapplication/PDF
999			_c12146 _d12145