Results 161 to 170 of about 5,516,106 (266)

Exploring the variable importance in random forests under correlations: a general concept applied to donor organ quality in post-transplant survival. [PDF]

BMC Med Res Methodol, 2023
Wies C, Miltenberger R, Grieser G, Jahn-Eimermacher A.   +3 more
europepmc   +1 more source

Photometric Redshift Estimation on SDSS Data Using Random Forests

, 2007
Samuel Carliles, Tamás Budavári, S. Heinis, Carey E. Priebe, Alexander S. Szalay   +4 more
openalex   +2 more sources

Toward Digital Staining using Imaging Mass Spectrometry and Random Forests [PDF]

, 2009
Michael Hanselmann, Ullrich Köthe, Marc Kirchner, Bernhard Y. Renard, Erika R. Amstalden, Kristine Glunde, Ron M. A. Heeren, Fred A. Hamprecht   +7 more
openalex   +1 more source

GARF: towards self-optimised random forests [PDF]

, 2012
Bader, Mohamed, Gaber, M.
core   +1 more source

Exploring the spatiotemporal influence of climate on American avian migration with random forests. [PDF]

Sci Rep
Bick IA, Bakkestuen V, Pedersen M, Raja K, Sethi S.   +4 more
europepmc   +1 more source

A Hybrid of Random Forests and Generalized Path Analysis: A Causal Modeling of Crashes in 52,524 Suburban Areas. [PDF]

J Res Health Sci, 2023
Jahanjoo F, Sadeghi-Bazargani H, Mansournia MA, Hosseini ST, Asghari-Jafarabadi M.   +4 more
europepmc   +1 more source

Implementation of the Random Forest method for the Imaging Atmospheric Cherenkov Telescope MAGIC

, 2008
J. Albert, E. Aliu, H. Anderhub, P. Antoranz, A. Armada, M. Asensio, C. Baixeras, J. A. Barrio, H. Bartko, D. Bastieri, J. A. Becker, W. Bednarek, K. Berger, C. Bigongiari, A. Biland, R. K. Böck, P. Bordas, V. Bosch‐Ramon, T. Bretz, I. Britvitch, Montaña Cámara, E. Carmona, A. Chilingarian, S. Ciprini, J. A. Coarasa, S. Commichau, J. L. Contreras, J. Cortina, M. T. Costado, V. Curtef, V. Danielyan, F. Dazzi, A. De Angelis, C. Delgado Mendez, R. de los Reyes, B. De Lotto, E. Domingo-Santamaría, D. Dorner, M. Doro, M. Errando, M. Fagiolini, D. Ferenc, E. Fernández, R. Firpo, J. Flix, M. V. Fonseca, L. Font, M. Fuchs, N. Galante, R. J. Garcı́a López, M. Garczarczyk, M. Gaug, M. Giller, F. Göebel, D. Hakobyan, M. Hayashida, T. Hengstebeck, A. Herrero, D. Höhne, J. Hose, Stefan Huber, C. C. Hsu, P. Jacoń, T. Jogler, R. Kosyra, D. Kranich, R. Kritzer, A. Laille, E. Lindfors, S. Lombardi, F. Longo, J. López, Marcos López, E. Lorenz, P. Majumdar, G. Maneva, K. Mannheim, M. Mariotti, M. Martı́nez, D. Mazin, C. Merck, M. Meucci, M. Meyer, J. M. Miranda, R. Mirzoyan, S. Mizobuchi, A. Moralejo, D. Nieto, K. Nilsson, J. Ninković, E. de Oña Wilhelmi, A. N. Otte, R. Mirzoyan, M. Panniello, R. Paoletti, J. M. Paredes, M. Pasanen, D. Pascoli, F. Pauss, R. Pegna   +99 more
openalex   +2 more sources

Artificial intelligence strategies based on random forests for detecting ischemia-reperfusion injury changes in kidney tissue during intravital imaging. [PDF]

Sci Rep
Pantic I, Paunovic Pantic J, Valjarevic S, Cumic J, Qin P, Corridon PR.   +5 more
europepmc   +1 more source

Computation of a probabilistic uranium concentration map of Norway: A digital expert elicitation approach employing random forests and artificial neural networks. [PDF]

Heliyon, 2023
Paasche H, Wang Y, Chand Baranwal V, Brönner M.   +3 more
europepmc   +1 more source

Random survival forests

, 2021
Survival Analysis is a crucial problem in statistics that tries to explain and model the behaviour of the individuals of a population through some features, one of them the time elapsed until death occurs. In this work, different models applied in survival analysis are reviewed, from the most traditional estimators to some actual algorithms based in ...
openaire   +1 more source