000			01731cam a22003257a 4500
001			17609682
005			20141216150759.0
008			130131r20122014xxkadk fr2b f001 0 eng d
010			_a2012289353
020			_a9781107096394 (hbk.)
020			_a1107096391 (hbk.)
020			_a9781107422223 (pbk.)
020			_a1107422221 (pbk.)
040			_aUKMGB _beng _cUKMGB _dBTCTA _dOCLCO _dBDX _dYDXCP _dCDX _dZWZ _dEYM _dTEF _dJHE _dMUU _dDLC _dEG-ScBUE
082	0	0	_a006.31 _222 _bFLA
100	1		_aFlach, Peter A. _936945
245	1	0	_aMachine learning : _bthe art and science of algorithms that make sense of data / _cPeter Flach.
250			_a1st ed., _breprinted.
260			_aCambridge, United Kingdom : _bCambridge University Press, _c2012.
300			_axvii, 396 p. : _bcharts, forms, tables ; _c25 cm.
500			_aReprint of the 2012 ed.
500			_aIndex : p. 383-396.
504			_aBibliography : p. 367-381.
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	3		_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 _936946
653			_bENGELC _bCOMSCI _cDecember2014
655			_vreading book _934232
942			_2ddc _k006.31 FLA
999			_c18786 _d18758