A comparison of random forests, boosting and support vector machines for genomic selection
Genomic selection (GS) involves estimating breeding values using molecular markers spanning the entire genome. Accurate prediction of genomic breeding values (GEBVs) presents a central challenge to contemporary plant and animal breeders. The existence of a wide array of marker-based approaches for p...
| Main Authors: | , , |
|---|---|
| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Springer
2011
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/3795 |
| _version_ | 1855524024396808192 |
|---|---|
| author | Ogutu, Joseph O. Piepho, Hans-Peter Schulz-Streeck, T. |
| author_browse | Ogutu, Joseph O. Piepho, Hans-Peter Schulz-Streeck, T. |
| author_facet | Ogutu, Joseph O. Piepho, Hans-Peter Schulz-Streeck, T. |
| author_sort | Ogutu, Joseph O. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Genomic selection (GS) involves estimating breeding values using molecular markers spanning the entire genome. Accurate prediction of genomic breeding values (GEBVs) presents a central challenge to contemporary plant and animal breeders. The existence of a wide array of marker-based approaches for predicting breeding values makes it essential to evaluate and compare their relative predictive performances to identify approaches able to accurately predict breeding values. We evaluated the predictive accuracy of random forests (RF), stochastic gradient boosting (boosting) and support vector machines (SVMs) for predicting genomic breeding values using dense SNP markers and explored the utility of RF for ranking the predictive importance of markers for pre-screening markers or discovering chromosomal locations of QTLs. |
| format | Journal Article |
| id | CGSpace3795 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2011 |
| publishDateRange | 2011 |
| publishDateSort | 2011 |
| publisher | Springer |
| publisherStr | Springer |
| record_format | dspace |
| spelling | CGSpace37952024-05-01T08:17:07Z A comparison of random forests, boosting and support vector machines for genomic selection Ogutu, Joseph O. Piepho, Hans-Peter Schulz-Streeck, T. forestry genetics Genomic selection (GS) involves estimating breeding values using molecular markers spanning the entire genome. Accurate prediction of genomic breeding values (GEBVs) presents a central challenge to contemporary plant and animal breeders. The existence of a wide array of marker-based approaches for predicting breeding values makes it essential to evaluate and compare their relative predictive performances to identify approaches able to accurately predict breeding values. We evaluated the predictive accuracy of random forests (RF), stochastic gradient boosting (boosting) and support vector machines (SVMs) for predicting genomic breeding values using dense SNP markers and explored the utility of RF for ranking the predictive importance of markers for pre-screening markers or discovering chromosomal locations of QTLs. 2011-12 2011-06-01T05:58:03Z 2011-06-01T05:58:03Z Journal Article https://hdl.handle.net/10568/3795 en Open Access Springer Ogutu, J.O., Piepho, H.-P. and Schulz-Streeck, T. 2011. A comparison of random forests, boosting and support vector machines for genomic selection. BMC Proceeding 5(Suppl 3):S11. |
| spellingShingle | forestry genetics Ogutu, Joseph O. Piepho, Hans-Peter Schulz-Streeck, T. A comparison of random forests, boosting and support vector machines for genomic selection |
| title | A comparison of random forests, boosting and support vector machines for genomic selection |
| title_full | A comparison of random forests, boosting and support vector machines for genomic selection |
| title_fullStr | A comparison of random forests, boosting and support vector machines for genomic selection |
| title_full_unstemmed | A comparison of random forests, boosting and support vector machines for genomic selection |
| title_short | A comparison of random forests, boosting and support vector machines for genomic selection |
| title_sort | comparison of random forests boosting and support vector machines for genomic selection |
| topic | forestry genetics |
| url | https://hdl.handle.net/10568/3795 |
| work_keys_str_mv | AT ogutujosepho acomparisonofrandomforestsboostingandsupportvectormachinesforgenomicselection AT piephohanspeter acomparisonofrandomforestsboostingandsupportvectormachinesforgenomicselection AT schulzstreeckt acomparisonofrandomforestsboostingandsupportvectormachinesforgenomicselection AT ogutujosepho comparisonofrandomforestsboostingandsupportvectormachinesforgenomicselection AT piephohanspeter comparisonofrandomforestsboostingandsupportvectormachinesforgenomicselection AT schulzstreeckt comparisonofrandomforestsboostingandsupportvectormachinesforgenomicselection |