Genomic selection accuracy of tolerance index based on biomass reduction under SCN infestation using 5 statistical models (rrBLUP: ridge regression best linear unbiased predictor, gBLUP: genomic best linear unbiased predictor, BLR: Bayesian Lasso regression, RF: random forest, and SVMs: support vector machines), four SNP sets (all SNPs, SMR_SNPs, MLM_PCA_SNPs, and MLM_PCA_K_SNPs), and different levels of cross-validation (2-fold, 3-fold, 4-fold, 5-fold, 6-fold, and 7-fold) with a total of 100 replications each.
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https://figshare.com/articles/dataset/Genomic_selection_accuracy_of_tolerance_index_based_on_biomass_reduction_under_SCN_infestation_using_5_statistical_models_rrBLUP_ridge_regression_best_linear_unbiased_predictor_gBLUP_genomic_best_linear_unbiased_predictor_BLR_Bayesian_Lasso/12665279
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资源简介：
Genomic selection accuracy of tolerance index based on biomass reduction under SCN infestation using 5 statistical models (rrBLUP: ridge regression best linear unbiased predictor, gBLUP: genomic best linear unbiased predictor, BLR: Bayesian Lasso regression, RF: random forest, and SVMs: support vector machines), four SNP sets (all SNPs, SMR_SNPs, MLM_PCA_SNPs, and MLM_PCA_K_SNPs), and different levels of cross-validation (2-fold, 3-fold, 4-fold, 5-fold, 6-fold, and 7-fold) with a total of 100 replications each.
创建时间：
2020-07-16
