000			01819cam a22003494a 4500
005			20150623165357.0
008			131022s2011 maua b 001 0 eng
020			_a0123748569
020			_a9780123748560
040			_aDLC _beng _cDLC _dYDX _dBTCTA _dYDXCP _dBWX _dDEBSZ _dCDX _dIUL _dDLC
042			_apcc
060			_a006.3'12 _bW D
082	0	0	_a006.3'12 _222
084			_a006.3'12 _bW D
100	1		_aWitten, I. H. _q(Ian H.)
245	1	0	_aData mining _h[[Book] :] _bpractical machine learning tools and techniques / _cIan H. Witten, Eibe Frank, Mark A. Hall.
250			_a3rd ed.
260			_aBurlington, MA : _bMorgan Kaufmann, _cc2011.
300			_axxxiii, 629 p. : _bill. ; _c24 cm.
490	1		_a[Morgan Kaufmann series in data management systems]
504			_aIncludes bibliographical references (p. 587-605) and index.
505	0		_aPart I. Machine Learning Tools and Techniques: 1. What's iIt all about?; 2. Input: concepts, instances, and attributes; 3. Output: knowledge representation; 4. Algorithms: the basic methods; 5. Credibility: evaluating what's been learned -- Part II. Advanced Data Mining: 6. Implementations: real machine learning schemes; 7. Data transformation; 8. Ensemble learning; 9. Moving on: applications and beyond -- Part III. The Weka Data MiningWorkbench: 10. Introduction to Weka; 11. The explorer -- 12. The knowledge flow interface; 13. The experimenter; 14 The command-line interface; 15. Embedded machine learning; 16. Writing new learning schemes; 17. Tutorial exercises for the weka explorer.
650		0	_aData mining.
700	1		_aHall, Mark A.
700	1		_aFrank, Eibe.
830		0	_aMorgan Kaufmann series in data management systems.
900	1		_aWitten, Ian Hugh.
990	1	0	_a90001a _b10001aq
001			0000115973
003			0000
942			_cBK
999			_c21985 _d21985