Sentence examples for trait training from inspiring English sources

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Meuwissen et al. [ 1] presented a two-step approach to predict genomic breeding values (GEBVs): First, SNP effects are estimated using genotyped individuals that are phenotyped for the quantitative trait (training), and then GEBVs are predicted for any genotyped individual by using only its SNP genotypes and estimated SNP effects.

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Safe microfinance institutions recruit the right kind of staff (in terms of values, education and personality traits), train them carefully in both the hard core (credit analysis procedures) and soft core (corporate purpose, people skills) of the business.

The GRU architecture is a newer and lighter alternative to the widely adopted LSTM, with two trainable gates instead of the latter's three resulting in less parameters to optimise, a desirable trait when training data are scarce.

First, SNP marker effects must be estimated from an analysis of a population with SNP genotypes and trait phenotypes (training set).

These SNP panels can be used to produce direct genomic values (DGV), as proposed by Meuwissen et al. [ 1], via the estimation of marker effects from the analysis of a population with SNP genotypes and trait phenotypes (training set).

Changes in RP also varied within the groups, suggesting that some individuals may have been better at performing the 15-s peak power ergometer test or possess the innate physiological traits or training acumen to achieve high rowing powers.

Realistically, this combination of traits and training is hardly common.

Relative to trait-targeted training population, the use of a large diverse training population could reduce inbreeding, probably at the expense of prediction accuracy.

We predicted DGV for six traits using training populations of various sizes and alternative Bayesian models for a population of 3240 crossbred animals.

Although these differences were not significant, these trends agree with the literature [ 11, 18]. Figure 4 shows the accuracies of pedigree and genomic EBV per generation, averaged over the 16 traits, when training only on data up to generation one.

Build on and reward these positive traits when training your puppy.

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