000			02020nam a22003137a 4500
005			20250918232719.0
008			131212s2012 enka b 001 0 eng d
020			_a9781107096394 (hbk.) _cRM387.00
039		9	_a201401070957 _brosli _y12-12-2013 _zrahah
040			_aUKMGB _beng _cUKMGB _dBTCTA _dOCLCO _dBDX _dYDXCP _dCDX _dZWZ _dEYM _dTEF _dJHE _dMUU _dDLC _dUKM
090			_aQ325.5.F533 3
090			_aQ325.5 _b.F533 3
100	1		_aFlach, Peter A.
245	1	0	_aMachine learning : _bthe art and science of algorithms that make sense of data / _cPeter Flach.
260			_aCambridge : _bCambridge University Press, _c2012.
300			_axvii, 396 p. : _bcol. ill. ; _c25 cm.
504			_aIncludes bibliographical references (p. 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	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.
907			_a.b15787679 _b2019-11-12 _c2019-11-12
942			_c01 _n0 _kQ325.5.F533 3
914			_avtls003546743
990			_ark4
991			_aFakulti Teknologi Sains Maklumat
998			_al _b2013-12-12 _cm _da _feng _genk _y0 _z.b15787679
999			_c558898 _d558898