000			01736nam a22002537a 4500
003			OSt
005			20220726095642.0
008			220726b |||||||| |||| 00| 0 eng d
020			_a9780123748560
040			_ckinley
082			_a006.312 WIT
100			_aWitten, I. H.
245			_aData mining : _bpractical machine learning tools and techniques / _cIan. H Witten ... [et al.].
250			_a3rd ed.
260			_aAmsterdam : _bMorgan Kaufmann, _c2011.
300			_axxxi, 629 p. : _bill. ; _c23 cm.
504			_aIncludes bibliographical references and index.
520			_a Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research.
650			_aData mining.
650			_aComputers _vData Mining. _xDatabase Management
700			_a Frank, Eibe.
700			_aHall, Mark A.
942			_2ddc _cBK
999			_c15520 _d15520