A zero altered Poisson random forest model for genomic-enabled prediction

In genomic selection choosing the statistical machine learning model is of paramount importance. In this paper, we present an application of a zero altered random forest model with two versions (ZAP_RF and ZAPC_RF) to deal with excess zeros in count response variables. The proposed model was compare...

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Detalles Bibliográficos
Autores principales: Montesinos-López, Osval Antonio, Montesinos-López, Abelardo, Mosqueda-Gonzalez, Brandon A, Montesinos-López, José Cricelio, Crossa, José, Ramirez, Nerida Lozano, Singh, Pawan, Valladares-Anguiano, Felícitas Alejandra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Investigation
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8022945/
https://www.ncbi.nlm.nih.gov/pubmed/33693599
http://dx.doi.org/10.1093/g3journal/jkaa057

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8022945/
https://www.ncbi.nlm.nih.gov/pubmed/33693599
http://dx.doi.org/10.1093/g3journal/jkaa057

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