000			01866nam a22002297a 4500
005			20241223114258.0
008			241223b |||||||| |||| 00| 0 eng d
020			_a9780128042915
040			_cNational Institute of Technology Goa
082			_a006.3 _bWIT/DAT
100			_aWitten, Ian H
110			_aFrank, Eibe
111			_aHall, Mark A
245			_aData mining: practical machine learning tools and techniques
250			_a4th
260			_aAmsterdam: _b Elsevier Morgan Kaufmann Publishers, _c 2017
300			_axxxii, 629p.: 11x20x1.5; Paperback
520			_aAbout the book: Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches. Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.
650			_2Computer Science Engineering _aComputer Science Engineering; Data mining and machine learning; Clustering; Hyperparameter selection; Bayesian networks; Autoencoders; Web mining; The explorer
700			_aPal, Christopher J
942			_2ddc _cBK _n0
999			_c5198 _d5198