Controlling the Overfitting of Heritability in Genomic Selection through Cross Validation
نویسندگان
چکیده
منابع مشابه
Preventing "Overfitting" of Cross-Validation Data
Suppose that, for a learning task, we have to select one hypothesis out of a set of hypotheses (that may, for example, have been generated by multiple applications of a randomized learning algorithm). A common approach is to evaluate each hypothesis in the set on some previously unseen cross-validation data, and then to select the hypothesis that had the lowest cross-validation error. But when ...
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The success of genomic selection mainly depends on the extent of linkage disequilibrium (LD) between markers and quantitative trait loci (QTL), number of QTL and heritability (h2) of the traits. The extent of LD depends on the genetic structure of the population and marker density. This study was conducted to determine the effects of marker density, level of heritability, number of QTL, and to ...
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The aim of this study was to determine the effect of marker density, level of heritability, number of QTLs, and size of training set on the genomic accuracy over three generations. Thereby, a trait was simulated with heritability of 0.10, 0.25 or 0.40. For each animal, a genome with 20 chromosomes, 1 Morgan each, was simulated. Different marker densities (2000, 4000 and 6000 markers) and 400 an...
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ژورنال
عنوان ژورنال: Scientific Reports
سال: 2017
ISSN: 2045-2322
DOI: 10.1038/s41598-017-14070-z