000			01994cam a22003371a 4500
003			OCoLC
005			20220928164128.0
008			101005t20112011maua b 001 0 eng
020			_a9780123748560 _q(pbk.)
020			_a0123748569 _q(pbk.)
035			_a(OCoLC)262433473
040			_beng _cUFH _dGSU _erda
050	0	0	_aQA76.9. _bWIT
082	0	0	_a006.3/12 _222
100	1		_aWitten, I. H. _q(Ian H.) _0http://id.loc.gov/authorities/names/n80102097. _eauthor.
245	1	0	_aData mining : _bpractical machine learning tools and techniques. _cIan H. Witten, Eibe Frank, Mark A. Hall.
250			_aThird edition /
264		1	_aAmsterdam, Netherlands : _bElsevier/Morgan Kaufmann, _c[2011]
264		4	_c©2011.
300			_axxxiii, 629 pages : _billustrations ; _c24 cm.
336			_atext _btxt _2rdacontent.
337			_aunmediated _bn _2rdamedia.
338			_avolume _bnc _2rdacarrier.
504			_aIncludes bibliographical references (pages 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. _0http://id.loc.gov/authorities/subjects/sh97002073.
700	1		_aFrank, Eibe. _0http://id.loc.gov/authorities/names/n99831139. _eauthor.
700	1		_aHall, Mark A. _q(Mark Andrew) _0http://id.loc.gov/authorities/names/no2011034315. _eauthor.
942			_2lcc _cBK _n0
999			_c1333 _d1333