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...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Veröffentlicht in:G3 (Bethesda)
Hauptverfasser: 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
Format: Artigo
Sprache:Inglês
Veröffentlicht: Oxford University Press 2020
Schlagworte:
Investigation
Online Zugang:https://ncbi.nlm.nih.gov/pmc/articles/PMC8022945/
https://ncbi.nlm.nih.gov/pubmed/33693599
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/g3journal/jkaa057
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