Sentence examples for the classification one from inspiring English sources

In a news release, Rouse said the classification — one his predecessor had declined to make — was based on a review of all available evidence and a review of court transcripts.

Émilion chateaus: one demoted from the classification, one raised from the lowest to the middle rank and one that held onto its ranking.

We had two considerations for the classification: one is that we used the quartiles of annual family income per capita to determine the approximate boundaries for each group; the other is we chose 2300 yuan as the upper limit for the first group given, that the Chinese poverty line is 2300 yuan.

In this work, we primarily exploit the ranking capabilities of naive Bayes classifiers [30] rather than the classification ones, in order to provide the most probable mature miRNA candidate(s) within a miRNA precursor sequence.

I know it is hard, very hard, to see past the classifications one is accustomed to, but allow me to try, on the subject of Benedict, in order to help gauge the contribution of his papacy, and the work that remains to be done by the next pope.

To assess the legitimacy of this classification one must distinguish between using the words ["unlawful" combatant] to denote a concept / notion and using the term ["unlawful combatant"] to denote a distinct label.

In the distinct classification, one of the two possible generations of birth was randomly chosen to assign phantom parents to genetic groups for animals with simulated uncertainty, whereas the phantom parents were assigned to both possible genetic groups in the fuzzy classification.

The critical difference between these classification systems is that, according to the ECLIPSE classification, one hospitalization (severe exacerbation) would suggest an infrequent exacerbator, whereas it would suggest a high-risk exacerbator according to the new GOLD classification [ 6, 8].

After the latter classification, one has three types of regions: environmental area, road region, and obstacles.

In many data mining and machine learning applications, there are two objectives in the task of classification; one is decreasing the test cost, the other is improving the classification accuracy.

That is, by examining the magnitude of the index of classification, one is able to determine the primary and secondary degrees.