000			02179cam a2200385Ii 4500
001			ocn925990514
003			OCoLC
005			20221215125202.0
007			ta
008			150921s2020 enka b 001 0 eng d
020			_a9780273769224 _q(paperback)
035			_a(OCoLC)925990514
040			_aYDXCP _beng _erda _cYDXCP _dOCLCQ _dQGK _dYDXIT _dOCLCF _dRDF _dOCLCO _dS2H
082	0	4	_a006.312 _223 _bTAN
100	1		_aTan, Pang-Ning. _eauthor.
245	1	0	_aIntroduction to data mining /
250			_aSecond edition, global edition.
264		1	_aHarlow : _bPearson Education, _c[2020]
300			_a859 pages : _billustrations ; _c24 cm
336			_atext _btxt _2rdacontent
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
504			_aIncludes bibliographical references and indexes.
505	0		_aIntroduction - Data - Classification: Basic Concepts and Techniques - Association Analysis: Basic Concepts and Algorithms - Cluster Analysis: Basic Concepts and Algorithms - Classification: Alternative Techniques - Association Analysis: Advanced Concepts - Cluster Analysis: Additional Issues and Algorithms - Anomaly Detection - Avoiding False Discoveries - Author Index - Subject Index - Copyright Permissions.
520	8		_aIntroduction to Data Mining, Second Edition, is intended for use in the Data Mining course. Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each concept is explored thoroughly and supported with numerous examples. The text requires only a modest background in mathematics. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms.
650		0	_aData mining.
650		0	_aArtificial intelligence _9721
650		0	_aMachine learning _944988
700	1		_aSteinbach, Michael, _eauthor.
700	1		_aKarpatne, Anuj, _eauthor.
700	1		_aKumar, Vipin, _d1956- _eauthor.
942			_2ddc _cSG_1
948			_hNO HOLDINGS IN LQI - 10 OTHER HOLDINGS
999			_c271754 _d271754