Sentence examples for random agreements from inspiring English sources

To account for random agreements Cohen's kappa was also calculated.

Values of Kappa close to 0 correspond to random agreements whereas values close to 1 represent perfect agreement.

Our goal was to obtain IAA for a reasonable amount of papers, while ensuring at least three annotators per paper, so as to minimize the chance of random agreements.

By having different phases of corpus development, with a varied number of annotators for each phase and subset of the corpus as well as a large number of classification categories, we believe that we have minimized the chance of random agreements and hard case bias.

They emphasize the importance of requiring the agreement between more than two annotators, which reduces both the chance of random agreements as well as hard case bias, whereby a classifier tends to model the pattern of bias of a particular annotator for instances which are hard to predict.

So the state called in a company that turns technology against the cheats: it analyzes answer sheets by computer and flags those with so many of the same questions wrong or right that the chances of random agreement are astronomically small.

Inter-rater agreement was 90%, and Cohen's Kappa (which takes into account the rate of random agreement) was.80, which is in the acceptable to good range.

Cohen's kappa ( k ) is calculated on the basis of the observed agreement p 0 between two raters and the random agreement p e expected for statistically independent decisions of both raters: ( k=frac{p_0-{p}_e}{1-{p}_e} ).

The automatic annotation was also evaluated in relation to that by a human annotator, by calculating the Kappa coefficient (K) [37] as follows: begin{aligned} K=frac{P(A -P(E)}{1-P(E)} end{A -PnEd}where (P(A)) is pairwise agreement and (P(E)) is random agreement.

Specifically, imputation accuracy, a measure of the concordance rate between the imputed and observed genotypes for each SNP, dramatically over-estimates reliability when minor allele frequencies are low and does not address the inflation of false positive rates arising from imputation error due to random agreement.

Nonetheless, it is a robust measure since it takes into account random agreement occurring by chance.