000			01815cam a2200337 i 4500
001			17609682
005			20230618091724.0
008			130131s2012 enka b 001 0 eng d
010			_a 2012289353
016	7		_a016098961 _2Uk
020			_a9781107422223 _qpaperback
020			_a1107422221 _qpaperback
035			_a(OCoLC)ocn795181906
040			_aUKMGB _beng _cUKMGB _dBTCTA _dOCLCO _dBDX _dYDXCP _dCDX _dZWZ _dEYM _dTEF _dJHE _dMUU _dEG-CaTKH _erda
042			_alccopycat
050	0	0	_aQ325.5 _b.F53 2012
082	0	0	_a006.31 FA.M 2012 _223
100	1		_aFlach, Peter A., _eauthor.
245	1	0	_aMachine learning : _bthe art and science of algorithms that make sense of data / _cPeter Flach.
264		1	_aCambridge : _bCambridge University Press, _c2012.
300			_axvii, 396 pages : _bcolor illustrations ; _c25 cm.
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
504			_aIncludes bibliographical references (pages 367-381) and index.
505	0		_a1. The ingredients of machine learning -- 2. Binary classification and related tasks -- 3. Beyond binary classification -- 4. Concept learning -- 5. Tree models -- 6. Rule models -- 7. Linear models -- 8. Distance-based models -- 9. Probabilistic models -- 10. Features -- 11. Model ensembles -- 12. Machine learning experiments -- Epilogue: where to go from here.
520			_a'Machine Learning' brings together all the state-of-the-art methods for making sense of data. With hundreds of worked examples and explanatory figures, it explains the principles behind these methods in an intuitive yet precise manner and will appeal to novice and experienced readers alike.
650		0	_aMachine learning _vTextbooks.
942			_2ddc _cBK
998			_amona.romia _bP _d20230618
999			_c240 _d240