Sentence examples for datasets were generated with from inspiring English sources

Datasets were generated with 1,000 entries per variable, with the number of variables ranging from 100 to 10,000.

For each combination of the test functions, noise types, and SNR, 100 datasets were generated with a sample size of 1024.

To help students complete such challenging term projects, over 400 R datasets were generated, with some examples shown in Table 4.

All datasets were generated with Affymetrix U95Av2 arrays.

Two control datasets were generated with the idea of studying the effect of other parameters.

Complex datasets were generated with and without weighting of the PINs.

For each model, a spectrum of simulated datasets was generated with balanced sample sizes of either (200,400,800, or 1600) and 20 SNPs (n of which were modeled as predictive SNPs, the rest being non-predictive, "noise").

From 1 cluster (for the ERR_alpha_agonist, ROR_gamma_antagonist, and RXR_gamma_antagonist datasets) to 65 clusters (for the ER_alpha_agonist dataset) were generated, with an average of 18 clusters per dataset and a mean value of 7.8 ligands per cluster.

Records in each dataset were generated with errors typically found in administrative data.

Five imputed versions of the dataset were generated, with results computed for each of those datasets; results were then combined with Rubin's rules.

Their dataset was generated with the assistance of students who manually labeled 6000 reviews collected from Epinions.com, 1394 of which were labeled as review spam.