000			01932cam a22002897i 4500
005			20260112063324.0
010			_a2013-933452
020			_a9781461468486 (alk. paper)
039			_a201509101230 _bstaff _c201509101230 _d staff _y 201509101216 _z staff
082			_a519.5 _bKUH
100			_aKuhn, Max.
245			_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	_t General Strategies. _t A Short Tour of the Predictive Modeling Process -- _t Data Pre-processing -- _t Over-Fitting and Model Tuning -- _t Regression Models. _t Measuring Performance in Regression Models -- _t Linear Regression and Its Cousins -- _t Nonlinear Regression Models -- _t Regression Trees and Rule-Based Models -- _t A Summary of Solubility Models -- _t Case Study: Compressive Strength of Concrete Mixtures -- _t Classification Models. _t Measuring Performance in Classification Models -- _t Discriminant Analysis and Other Linear Classification Models -- _t Nonlinear Classification Models -- _t Classification Trees and Rule-Based Models -- _t A Summary of Grant Application Models -- _t Remedies for Severe Class Imbalance -- _t Case Study: Job Scheduling -- _t Other Considerations. _t Measuring Predictor Importance -- _t An Introduction to Feature Selection -- _t Factors That Can Affect Model Performance.
650			_aMathematical statistics.
650			_aMathematical models.
650			_aPrediction theory.
650			_aMathematical models. _2 fast
650			_aMathematical statistics. _2 fast
650			_aPrediction theory. _2 fast
700			_aJohnson, Kjell.
991			_aVIRTUA40
991			_aVTLSSORT0080*0100*0200*0820*1000*2450*2600*3000*5040*5050*6500*6501*6502*6503*6504*6505*7000*9992
909			_a5446
999			_c4905 _d4905