000			01594nam a2200229Ia 4500
003			MX-MdCICY
005			20250625124713.0
040			_cCICY
090			_aB-8085
245	1	0	_aClassification Tree Method for Bacterial Source Tracking with Antibiotic Resistance Analysis Data
490	0		_vApplied and Environmental MicroBiology, 72, p.3468-3475, 2006
520	3		_aVarious statistical classification methods, including discriminant analysis, logistic regression, and cluster analysis, have been used with antibiotic resistance analysis (ARA)data to construct models for bacterial source tracking (BST). We applied the statistical method known as classification trees to build a model for BST for the Anacostia Watershed in Maryland. Classification trees have more flexibility than other statistical lassification approaches based on standard statistical methods to accommodate complex interactions among ARA variables. This article describes the use of classification trees for BST and includes discussion of its principal parameters and features. Anacostia Watershed ARA data are used to illustrate the application of classification trees, and we report the BST results for the watershed.
700	1	2	_aPrice, B.
700	1	2	_aVenso, E.A.
700	1	2	_aFrana, M.F.
700	1	2	_aGreenberg, J.
700	1	2	_aWare, A.
700	1	2	_aCurrey, L.
856	4	0	_uhttps://drive.google.com/file/d/1Xc0JA54zsEFPba5TFrz2bLoR_WBWt5au/view?usp=drivesdk _zPara ver el documento ingresa a Google con tu cuenta: @cicy.edu.mx
942			_2Loc _cREF1
008			250602s9999 xx |||||s2 |||| ||und|d
999			_c42394 _d42394