000			03745cam a2200445 i 4500
001			on1006614275
003			OCoLC
005			20250612155447.0
006			m o d
007			cr |n|||||||||
008			171018s2018 enka ob 001 0 eng d
040			_aYDX _beng _erda _epn _cYDX _dN$T _dCNCGM _dOPELS _dUAB _dSNM _dD6H _dEBLCP _dCHVBK _dMERUC _dCUY _dUMR _dSNK _dUMR _dOCLCQ _dU3W _dINNDH _dRDF _dOCLCO _dOCLCF _dOCLCQ _dVT2 _dOCLCO _dOCLCQ _dOCLCO _dOCLCL
019			_a1006502593 _a1007049564 _a1007373020 _a1099430476 _a1235830451 _a1258397964
020			_a9780124166455 _q(electronic bk.)
020			_a0124166458 _q(electronic bk.)
020			_z9780124166325
020			_z0124166326
035			_a(OCoLC)1006614275 _z(OCoLC)1006502593 _z(OCoLC)1007049564 _z(OCoLC)1007373020 _z(OCoLC)1099430476 _z(OCoLC)1235830451 _z(OCoLC)1258397964
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080			_a519.6(021) Q8
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100	1		_aNisbet, Robert, _eauthor. _933983
245	1	0	_aHandbook of statistical analysis and data mining applications / _cauthors, Robert Nisbet, Gary Miner, Ken Yale ; guest authors of selected chapters, John Elder IV, Andy Peterson.
250			_aSecond edition.
264		1	_aLondon, United Kingdom : _bAcademic Press, an imprint of Elsevier, _c[2018]
300			_a1 online resource : _billustrations
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
504			_aIncludes bibliographical references and index.
505	0		_aHistory of phases of data analysis, basic theory, and the data mining process -- The algorithms in data mining and text mining, the organization of the three most common data mining tools, and selected specialized areas using data mining -- Tutorials--step-by-step case studies as a starting point to learn how to do data mining analyses -- Measuring true complexity, the "right model for the right use," top mistakes, and the future of analytics.
520			_aHandbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas-from science and engineering, to medicine, academia and commerce.
650		0	_aData mining _xStatistical methods. _933984
700	1		_aMiner, Gary, _eauthor. _933985
700	1		_aYale, Kenneth P., _d1956- _eauthor. _1https://id.oclc.org/worldcat/entity/E39PCjwr3vDCfp9MBqdWJhxjyd _933986
758			_ihas work: _aHandbook of statistical analysis and data mining applications (Text) _1https://id.oclc.org/worldcat/entity/E39PCGtpKb8dDJ3bTRhxHdRD7b _4https://id.oclc.org/worldcat/ontology/hasWork
776	0	8	_iPrint version: _aNisbet, Robert. _tHandbook of statistical analysis and data mining applications. _bSecond edition. _dLondon : Academic Press, [2018] _z9780124166325 _w(OCoLC)1012917853
856	4	0	_3ScienceDirect _uhttps://www.sciencedirect.com/science/book/9780124166325
999			_c216409 _d216409