Multivariate Statistical Machine Learning Methods for Genomic Prediction.
This book is open access under a CC BY 4.0 license This open access book brings together the latest genome base prediction models currently being used by statisticians, breeders and data scientists. It provides an accessible way to understand the theory behind each statistical learning tool, the req...
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Place / Publishing House: | Cham : : Springer International Publishing AG,, 2022. ©2022. |
Year of Publication: | 2022 |
Language: | English |
Physical Description: | 1 online resource (707 pages) |
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(CKB)5100000000193939 (MiAaPQ)EBC6855260 (Au-PeEL)EBL6855260 (OCoLC)1294143848 (oapen)https://directory.doabooks.org/handle/20.500.12854/78249 (PPN)260834084 (EXLCZ)995100000000193939 |
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Montesinos López, Osval Antonio. Multivariate Statistical Machine Learning Methods for Genomic Prediction. Cham Springer Nature 2022 Cham : Springer International Publishing AG, 2022. ©2022. 1 online resource (707 pages) text txt rdacontent computer c rdamedia online resource cr rdacarrier Description based on publisher supplied metadata and other sources. This book is open access under a CC BY 4.0 license This open access book brings together the latest genome base prediction models currently being used by statisticians, breeders and data scientists. It provides an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool. To do so, for each tool the book provides background theory, some elements of the R statistical software for its implementation, the conceptual underpinnings, and at least two illustrative examples with data from real-world genomic selection experiments. Lastly, worked-out examples help readers check their own comprehension. The book will greatly appeal to readers in plant (and animal) breeding, geneticists and statisticians, as it provides in a very accessible way the necessary theory, the appropriate R code, and illustrative examples for a complete understanding of each statistical learning tool. In addition, it weighs the advantages and disadvantages of each tool. English Bill and Melinda Gates Foundation Agricultural science bicssc Life sciences: general issues bicssc Botany & plant sciences bicssc Animal reproduction bicssc Probability & statistics bicssc open access Statistical learning Bayesian regression Deep learning Non linear regression Plant breeding Crop management multi-trait multi-environments models 3-030-89009-0 Montesinos López, Abelardo. Crossa, José. |
language |
English |
format |
eBook |
author |
Montesinos López, Osval Antonio. |
spellingShingle |
Montesinos López, Osval Antonio. Multivariate Statistical Machine Learning Methods for Genomic Prediction. |
author_facet |
Montesinos López, Osval Antonio. Montesinos López, Abelardo. Crossa, José. |
author_variant |
l o a m loa loam |
author2 |
Montesinos López, Abelardo. Crossa, José. |
author2_variant |
l a m la lam j c jc |
author2_role |
TeilnehmendeR TeilnehmendeR |
author_sort |
Montesinos López, Osval Antonio. |
title |
Multivariate Statistical Machine Learning Methods for Genomic Prediction. |
title_full |
Multivariate Statistical Machine Learning Methods for Genomic Prediction. |
title_fullStr |
Multivariate Statistical Machine Learning Methods for Genomic Prediction. |
title_full_unstemmed |
Multivariate Statistical Machine Learning Methods for Genomic Prediction. |
title_auth |
Multivariate Statistical Machine Learning Methods for Genomic Prediction. |
title_new |
Multivariate Statistical Machine Learning Methods for Genomic Prediction. |
title_sort |
multivariate statistical machine learning methods for genomic prediction. |
publisher |
Springer Nature Springer International Publishing AG, |
publishDate |
2022 |
physical |
1 online resource (707 pages) |
isbn |
3-030-89010-4 3-030-89009-0 |
callnumber-first |
S - Agriculture |
callnumber-subject |
S - General Agriculture |
callnumber-label |
S1-972 |
callnumber-sort |
S 11 3972 |
illustrated |
Not Illustrated |
oclc_num |
1294143848 |
work_keys_str_mv |
AT montesinoslopezosvalantonio multivariatestatisticalmachinelearningmethodsforgenomicprediction AT montesinoslopezabelardo multivariatestatisticalmachinelearningmethodsforgenomicprediction AT crossajose multivariatestatisticalmachinelearningmethodsforgenomicprediction |
status_str |
n |
ids_txt_mv |
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carrierType_str_mv |
cr |
is_hierarchy_title |
Multivariate Statistical Machine Learning Methods for Genomic Prediction. |
author2_original_writing_str_mv |
noLinkedField noLinkedField |
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1796651447935303680 |
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