Sentence examples for a selected training from inspiring English sources

A selected training task was implemented as a case study for further analysis based on laptop usage in the Fluid Science Laboratory (FSL) inside the Columbus module in the International Space Station (ISS).

Among the 974 genes belonging to the ξ matrix, we finally retained, for the final gene signature, in a ξ′ matrix, 322 genes as function of a threshold (P=0.001) on the frequencies of relevance, which is defined as the frequency at which a given gene and a given tumor are found together in a selected training matrix, weighted by the number of training tumors well classified by this training matrix.

The neural network model was trained using a carefully selected training signal that contained all the relevant process and controller dynamics.

To evaluate a query compound, we compute the cumulative probability (P(X le x)) of its distance D(c), which resembles the probability that a randomly selected training distance is less than or equal to the query compound distance.

When using 1%% of a randomly selected training data set we found that, surprisingly, the same parameters (C = 64, γ = 1, ε = 0.00391) were optimal for 10 out of 13 descriptor sets.

Models with 1 10 numbers of splits per chromosome were fitted to the genotypic and phenotypic data of a randomly selected training set of genotypes of size 800.

Multiple parameters derived from the copy numbers of ERBB2, MYC, CDKN2A, and ZNF217 were screened by univariate log-rank analysis of overall survival at multiple cutoff values within a randomly selected training subset, as described in the Materials and Methods section.

As indicated in research design and methods, tree models and decision rules were developed to predict GDRadj based on a randomly selected training set (n = 125) followed by evaluating the performance of the models in the remaining testing set (n = 42).

Each of the trees was trained and evaluated on a different, randomly selected training set test set pair.

Each of the t trees in the inner loop is trained and evaluated on a different, randomly selected training and test data sets.

In our implementation of the QUICKRBF package, the user can specify the number of hidden nodes to be incorporated and then the learning algorithm will place the activation functions at a set of randomly selected training samples.