000			01922cam a22003494a 4500
001			16490354
003			BD-ChPU
005			20250120112536.0
008			101005s2011 maua b 001 0 eng
010			_a 2010039827
020			_a9780123748560 (pbk.)
035			_a(OCoLC)ocn262433473
040			_aDLC _cDLC _dYDX _dBTCTA _dYDXCP _dBWX _dDEBSZ _dCDX _dIUL _dDLC _dBD-ChPU _beng
042			_apcc
050	0	0	_aQA76.9.D343 _bW58 2011
082	0	0	_a006.3/12 W829d 2011 _222
100	1		_aWitten, I. H. _q(Ian H.)
245	1	0	_aData mining : _bpractical machine learning tools and techniques / _cIan H. Witten, Eibe Frank and Mark A. Hall.
250			_aThird edition.
260			_aBurlington, MA : _bMorgan Kaufmann, _cc2011.
300			_axxxiii, 629 pages : _billustrations ; _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.
526			_aComputer Science & Engineering
650		0	_aData mining. _95463
700	1		_aFrank, Eibe.
700	1		_aHall, Mark A.
830		0	_aMorgan Kaufmann series in data management systems.
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2ddc _cBK
999			_c7763 _d7763