Sentence examples for inflated training from inspiring English sources

Exact(2)

But here at the Good Law Project, we want to ask the courts to weigh it on the scales against indentured service for inflated training costs on unequal terms.

But the Fund noted in its press release that it is particularly concerned about inflated training expenses and theft of drugs.

Similar(58)

Freight shipments on the Trans-Siberian, however, experienced increasing problems over time with dilapidated rail infrastructures, theft, damaged freight, late trains, inflated freight fees, uncertain scheduling for return of containers and geopolitical tension.

In 1997, a former Loral employee told the government that Loral's Goodyear Aerospace unit had inflated costs in its flight-training programs for the F-15 fighter.

This approach lead to a conservative yet accurate identification of pathways in single genomes when compared with KEGG identifications (that are known to be inflated) and does not rely on training, so it appear more suitable for metagenomic data sets.

The fact that the Pre-diagnosis data was a subset of the full dataset meant that applying the All-data model to Pre-diagnosis observations would have artificially inflated accuracy, due to information leakage between training and test data.

For instance, Ben-Hur and Noble found the performance of SVM classifiers trained with localization negatives artificially inflated because this negative set is composed entirely of high-confidence pairs [ 5, 33].

We find that using training labels obtained well after samples appear, and thus unavailable in practice for current training data, inflates measured detection by almost 20 percentage points.

But in most cases, educators blame the lack of use on inadequate training, tradition-bound teachers, a shortage of computers and inflated expectations.

As researchers have different background knowledge and may receive different, more intense training programs prior to conducting assessments, this may have artificially inflated the results leading to the high and more narrow range of estimates.

Gorjanc et al. [ 10] found inflated or shrunken estimates of genetic merit (depending on the number of SNPs in training and validation) and that these effects were more pronounced at low coverage.

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