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Performance of different prediction models for total carote..:
Ravena Rocha Bessa de Carvalho (12024672)
;
Diego Fernando Marmolejo Cortes (4827291)
;
Massaine Bandeira e Sousa (7866242)
..
https://figshare.com/articles/dataset/Performance_of_different_prediction_models_for_total_carotenoid_content_in_cassava_roots_using_colorimetric_indices_obtained_from_digital_images_considering_the_complete_model_all_variables_and_reduced_model_variables_with_more_than_50_rela/19098525. , 2022
Link:
https://doi.org/10.1371/journal.pone.0263326.t001
RT Journal T1
Performance of different prediction models for total carotenoid content in cassava roots using colorimetric indices obtained from digital images considering the complete model (all variables) and reduced model (variables with more than 50% relative importance), using the random cross-validation without test set (V-Random), PCA clustering-based cross-validation (IV-Cluster), and random cross-validation with test set (IV-Random)
UL https://suche.suub.uni-bremen.de/peid=base-ftsmithonian:oai:figshare.com:article_19098525&Exemplar=1&LAN=DE A1 Ravena Rocha Bessa de Carvalho (12024672) A1 Diego Fernando Marmolejo Cortes (4827291) A1 Massaine Bandeira e Sousa (7866242) A1 Luciana Alves de Oliveira (11985977) A1 Eder Jorge de Oliveira (8544567) YR 2022 K1 Biotechnology K1 Ecology K1 Sociology K1 Environmental Sciences not elsewhere classified K1 Biological Sciences not elsewhere classified K1 total carotenoids content K1 principal component analysis K1 best predictive ability K1 select predictive models K1 pca ) K1 correlation K1 94 ) K1 associated K1 228 biofortified genotypes K1 throughput phenotyping tools K1 developing prediction models K1 div >< p K1 digital image analysis K1 high positive correlation K1 use digital images K1 2 </ sup K1 tcc phenotyping tools K1 prediction models K1 significant correlation K1 l </ K1 cassava genotypes K1 blue images K1 based phenotyping K1 tcc estimates K1 tcc based K1 study aimed K1 square error K1 smallest error K1 short period K1 screening hundreds K1 results demonstrated K1 machine learning K1 international commission K1 important ones K1 extract information K1 effective alternative K1 diversity studies K1 data obtained K1 colorimetric data K1 cassava roots K1 biofortification program K1 analyzed using K1 >* parameter K1 24 ) JF https://figshare.com/articles/dataset/Performance_of_different_prediction_models_for_total_carotenoid_content_in_cassava_roots_using_colorimetric_indices_obtained_from_digital_images_considering_the_complete_model_all_variables_and_reduced_model_variables_with_more_than_50_rela/19098525 LK http://dx.doi.org/https://doi.org/10.1371/journal.pone.0263326.t001 DO https://doi.org/10.1371/journal.pone.0263326.t001 SF ELIB - SuUB Bremen
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