000			02223cam a22003977i 4500
001			17629633
003			ZET-ke
005			20210614151129.0
008			130219s2013 nyua b 001 0 eng d
010			_a 2013933452
020			_a9781461468486 (alk. paper)
020			_a1461468485 (alk. paper)
020			_z9781461468493 (ebk.)
035			_a(OCoLC)ocn827083441
040			_aYDXCP _beng _cZET-ke _dBTCTA _dDMF _dIXA _dOHX _dOCLCF _dZET-ke
042			_alccopycat
050	0	0	_aQA276 _b.K84 2013
072		7	_aQA _2lcco
100	1		_aKuhn, Max.
245	1	0	_aApplied predictive modeling / _cMax Kuhn, Kjell Johnson.
260			_aNew York : _bSpringer, _cc2013.
300			_axiii, 600 p. : _bill. (some col.) ; _c24 cm.
504			_aIncludes bibliographical references (pages 569-587) and index.
505	0	0	_tGeneral Strategies. _tA Short Tour of the Predictive Modeling Process -- _tData Pre-processing -- _tOver-Fitting and Model Tuning -- _tRegression Models. _tMeasuring Performance in Regression Models -- _tLinear Regression and Its Cousins -- _tNonlinear Regression Models -- _tRegression Trees and Rule-Based Models -- _tA Summary of Solubility Models -- _tCase Study: Compressive Strength of Concrete Mixtures -- _tClassification Models. _tMeasuring Performance in Classification Models -- _tDiscriminant Analysis and Other Linear Classification Models -- _tNonlinear Classification Models -- _tClassification Trees and Rule-Based Models -- _tA Summary of Grant Application Models -- _tRemedies for Severe Class Imbalance -- _tCase Study: Job Scheduling -- _tOther Considerations. _tMeasuring Predictor Importance -- _tAn Introduction to Feature Selection -- _tFactors That Can Affect Model Performance.
650		0	_aMathematical statistics. _9890
650		0	_aMathematical models.
650		0	_aPrediction theory.
650		7	_aMathematical models. _2fast
650		7	_aMathematical statistics. _2fast _9890
650		7	_aPrediction theory. _2fast
700	1		_aJohnson, Kjell.
906			_a7 _bcbc _ccopycat _d2 _encip _f20 _gy-gencatlg
942			_2lcc _cBK _hQA276 _i.K84 2013 _kQA276 _m.K84 2013
999			_c4948 _d4948