000			02403nam a2200337Ia 4500
003			MX-MdCICY
005			20250625160200.0
040			_cCICY
090			_aB-16911
245	1	0	_aRandom forests for classification in ecology
490	0		_vEcology, 88, p.2783-2792, 2007
520	3		_aClassification procedures are some of the most widely used statistical methods in ecology. Random forests (RF)is a new and powerful statistical classifier that is well established in other disciplines but is relatively unknown in ecology. Advantages of RF compared to other statistical classifiers include (1)very high classification accuracy; (2)a novel method of determining variable importance; (3)ability to model complex interactions among predictor variables; (4)flexibility to perform several types of statistical data analysis, including regression, classification, survival analysis, and unsupervised learning; and (5)an algorithm for imputing missing values. We compared the accuracies of RF and four other commonly used statistical classifiers using data on invasive plant species presence in Lava Beds National Monument, California, USA, rare lichen species presence in the Pacific Northwest, USA, and nest sites for cavity nesting birds in the Uinta Mountains, Utah, USA. We observed high classification accuracy in all applications as measured by cross-validation and, in the case of the lichen data, by independent test data, when comparing RF to other common classification methods. We also observed that the variables that RF identified as most important for classifying invasive plant species coincided with expectations based on the literature.
650	1	4	_aADDITIVE LOGISTIC REGRESSION
650	1	4	_aCLASSIFICATION TREES
650	1	4	_aLDA
650	1	4	_aLOGISTIC REGRESSION
650	1	4	_aMACHINE LEARNING
650	1	4	_aPARTIAL DEPENDENCE PLOTS
650	1	4	_aRANDOM FORESTS
650	1	4	_aSPECIES DISTRIBUTION MODELS
700	1	2	_aCutler, D. Richard
700	1	2	_aEdwards Jr., Thomas C.
700	1	2	_aBeard, Karen H.
700	1	2	_aCutler, Adele
700	1	2	_aHess, Kyle T.
700	1	2	_aGibson, Jacob
700	1	2	_aLawler, Joshua J.
856	4	0	_uhttps://drive.google.com/file/d/1A03Nq7vvoWl1RihizPFvdITi03jrU4WD/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			_c51076 _d51076