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).
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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
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资源简介：
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).
创建时间：
2022-01-31
