Genomic prediction using machine learning: a comparison of the performance of regularized regression, ensemble, instance-based and deep learning methods on synthetic and empirical data.
Saved in:
| Title: | Genomic prediction using machine learning: a comparison of the performance of regularized regression, ensemble, instance-based and deep learning methods on synthetic and empirical data. |
|---|---|
| Authors: | Lourenço VM; Center for Mathematics and Applications (NOVA Math) and Department of Mathematics, NOVA SST, 2829-516, Caparica, Portugal. vmml@fct.unl.pt., Ogutu JO; Institute of Crop Science, Biostatistics Unit, University of Hohenheim, Fruwirthstrasse 23, 70599, Stuttgart, Germany. jogutu2007@gmail.com., Rodrigues RAP; Center for Mathematics and Applications (NOVA Math) and Department of Mathematics, NOVA SST, 2829-516, Caparica, Portugal., Posekany A; Research Unit of Computational Statistics, Vienna University of Technology, Wiedner Hauptstr. 8-10, 1040, Vienna, Austria., Piepho HP; Institute of Crop Science, Biostatistics Unit, University of Hohenheim, Fruwirthstrasse 23, 70599, Stuttgart, Germany. |
| Source: | BMC genomics [BMC Genomics] 2024 Feb 07; Vol. 25 (1), pp. 152. Date of Electronic Publication: 2024 Feb 07. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: BioMed Central Country of Publication: England NLM ID: 100965258 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2164 (Electronic) Linking ISSN: 14712164 NLM ISO Abbreviation: BMC Genomics Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 1471-2164 |
|---|---|
| DOI: | 10.1186/s12864-023-09933-x |