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007			cr n
008			100920s2011 enka b 001 0 eng d
020			_a9780470688298 (hardback)
035			_a(WaSeSS)ssj0000476890
040			_aDLC _cDLC _dYDX _dYDXCP _dIUL _dCDX _dDLC _dWaSeSS _dBD-DhUL
042			_apcc
050		4	_aQA76.9.D343 _bT84 2011
082	0	0	_a006.312 _222 _bTUD
100	1		_aTuffery, Stéphane.
210	1	0	_aData mining and statistics for decision making
245	1	0	_aData mining and statistics for decision making / _cStéphane Tufféry.
260			_aChichester, West Sussex ; _aHoboken, NJ. : _bWiley, _c2011.
300			_axv, 689 p.: _bill. ; _c25 cm.
365			_aUS$ _b89.96
490	1		_aWiley series in computational statistics
504			_aIncludes bibliographical references and index.
505	0		_aOverview of data mining -- The development of a data mining study -- Data exploration and preparation -- Using commercial data -- Statistical and data mining software -- An outline of data mining methods -- Factor analysis -- Neural networks -- Cluster analysis -- Association analysis -- Classification and prediction methods -- An application of data mining: scoring -- Factors for success in a data mining project -- Text mining -- Web mining -- Appendix A: Elements of statistics -- Appendix B: further reading.
506			_aLicense restrictions may limit access.
520			_a"This practical guide to understanding and implementing data mining techniques discusses traditional methods--cluster analysis, factor analysis, linear regression, PLS regression, and generalized linear models--and recent methods--bagging and boosting, decision trees, neural networks, support vector machines, and genetic algorithm. The book focuses largely on credit scoring, one of the most common applications of predictive techniques, but also includes other descriptive techniques, such as customer segmentation. It also covers data mining with R, provides a comparison of SAS and SPSS, and includes an appendix presenting the necessary statistical background"-- _cProvided by publisher.
520			_a"Data Mining is a practical guide to understanding and implementing data mining techniques, featuring traditional methods such as cluster analysis, factor analysis, linear regression, PLS regression and generalised linear models"-- _cProvided by publisher.
650		0	_aData mining.
650		0	_aStatistical decision.
942			_2ddc _cBK
999			_c1289 _d1289