000			01771 a2200373 4500
001			72373
999			_c72373 _d20685
003			TR-AnTOB
005			20200607104530.0
008			081105s2005 ne a b 001 0 eng
010			_a2005043385
020			_a0120884070
020			_a9780120884070
040			_aDLC _cDLC _dBAKER _dIXA _dEGM _dMUQ _dNLGGC _dPL _dUBA _dYDXCP _dOCLCQ _dBTCTA _dUPP _dNMT
041			_aeng
042			_apcc
049			_aNMTA
050			_aQA76.9.D343 _bW58 2005
090			_aQA76.9.D343 W58 2005
100			_aWitten, I. H., _q(Ian H.) _948650
245		0	_aData mining : _bpractical machine learning tools and techniques / _cIan H. Witten, Eibe Frank.
250			_a2nd ed.
264		1	_aAmsterdam ; _aBoston, MA : _bMorgan Kaufman, _c2005.
300			_axxxi, 525 p. : _bill. ; _c24 cm.
490	0		_aMorgan Kaufmann series in data management systems.
504			_aIncludes bibliographical references (p. 485-503) and index.
505		0	_aPt. I. Machine learning tools and techniques. What's it all about? -- Input : concepts, instances, and attributes -- Output : knowledge representation -- Algorithms : the basic methods -- Credibility : evaluating what's been learned -- Implementations : real machine learning schemes -- Transformations : engineering the input and output -- Moving on : extensions and applications -- Pt. II. The Weka machine learning workbench. Introduction to Weka -- The Explorer -- The Knowledge Flow interface -- The Experimenter -- The command-line interface -- Embedded machine learning -- Writing new learning schemes.
650		7	_aVeri madenciliği _2etuturkob _94839
650		0	_aData mining _96146
700			_aFrank, Eibe _948651
902			_a0026475, 0026476
903			_aMerkez Kütüphane
945			_aMC, CS
942			_cBK