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Volumn 2, Issue , 2011, Pages 1343-1348

Incorporating boosted regression trees into ecological latent variable models

Author keywords

[No Author keywords available]

Indexed keywords

BIRD SPECIES; BOOSTED REGRESSION TREES; DIRECT MAPPING; EXPLICIT MODELS; FUNCTIONAL GRADIENT; LATENT STRUCTURES; LATENT VARIABLE METHODS; LATENT VARIABLE MODELS; LOGISTIC REGRESSION MODELS; NON-PARAMETRIC; NONPARAMETRIC METHODS; PARAMETRIC MODELS; REGRESSION TREES; TREE METHOD;

EID: 80055061923     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (44)

References (11)
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    • Dempster, A. P.; Laird, N. M.; and Rubin, D. B. 1977. Maximum Likelihood from Incomplete Data via the EM Algorithm. JRSS Ser. B 39(1):1-38.
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  • 3
    • 56349084627 scopus 로고    scopus 로고
    • Gradient Tree Boosting for Training Conditional Random Fields
    • Dietterich, T. G.; Hao, G.; and Ashenfelter, A. 2008. Gradient Tree Boosting for Training Conditional Random Fields. JMLR 9:2113-2139.
    • (2008) JMLR , vol.9 , pp. 2113-2139
    • Dietterich, T.G.1    Hao, G.2    Ashenfelter, A.3
  • 4
    • 33645917058 scopus 로고    scopus 로고
    • Novel methods improve prediction of species' distributions from occurrence data
    • Elith, J.; et al. 2006. Novel methods improve prediction of species' distributions from occurrence data. Ecography 29(2):129-151.
    • (2006) Ecography , vol.29 , Issue.2 , pp. 129-151
    • Elith, J.1
  • 5
    • 0035470889 scopus 로고    scopus 로고
    • Greedy function approximation: A gradient boosting machine
    • Friedman, J. 2001. Greedy function approximation: a gradient boosting machine. Annals of Statistics 29(5):1189-1232. (Pubitemid 33405972)
    • (2001) Annals of Statistics , vol.29 , Issue.5 , pp. 1189-1232
    • Friedman, J.H.1
  • 6
    • 77957064121 scopus 로고    scopus 로고
    • Predicting species distributions from checklist data using site-occupancy models
    • Kéry, M.; Gardner, B.; and Monnerat, C. 2010. Predicting species distributions from checklist data using site-occupancy models. J. Biogeo. 37:1851-1862.
    • (2010) J. Biogeo. , vol.37 , pp. 1851-1862
    • Kéry, M.1    Gardner, B.2    Monnerat, C.3
  • 7
    • 0000989596 scopus 로고    scopus 로고
    • Estimating site occupancy rates when detection probabilities are less than one
    • MacKenzie, D. I.; Nichols, J. D.; Lachman, G. B.; Droege, S.; Royle, J. A.; and Langtimm, C. A. 2002. Estimating Site Occupancy Rates When Detection Probabilities Are Less Than One. Ecology 83(8):2248-2255. (Pubitemid 36524763)
    • (2002) Ecology , vol.83 , Issue.8 , pp. 2248-2255
    • MacKenzie, D.I.1    Nichols, J.D.2    Lachman, G.B.3    Droege, S.4    Royle, J.A.5    Langtimm, C.A.6
  • 11
    • 79951759672 scopus 로고    scopus 로고
    • Modeling Experts and Novices in Citizen Science data for Species Distribution Modeling
    • Yu, J.; Wong, W.-K.; and Hutchinson, R. A. 2010. Modeling Experts and Novices in Citizen Science data for Species Distribution Modeling. In ICDM 2010.
    • (2010) ICDM 2010
    • Yu, J.1    Wong, W.-K.2    Hutchinson, R.A.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.