Sentence examples for minimal misclassification of from inspiring English sources

Face-to-face interviews with each participant should have resulted in minimal misclassification of ethnic subgroup.

Further, we capture the type of anesthesia based on charge codes, which should result in minimal misclassification of exposure.

Results from these sensitivity analyses were similar to the primary analysis, indicating minimal misclassification of unexposed patients as exposed and prevalent users as new users.

Such a small increase would have resulted in minimal misclassification of individuals to BMI categories in the years following survey response in this study.

However, comparing baseline self-reported diabetes with objective information about the use of diabetes medication from wave 0 indicated minimal misclassification of cases of diagnosed diabetes.

The value of zero was chosen in the training case (VACV-COP) because it represented a reasonable cut-off between genes that were known to be major and ORFs that were known to be minor with minimal misclassification of genes.

(iii) To select the smallest possible set of genes for minimal misclassification error rate, out-of-bag error rates using the N RF classifiers sequentially fitted using the top M (M = 1, …, N) variables were obtained and contrasted.

An appealing recommendation [ 17] to employ both minimal misclassification rate (instead of.

Recruitment of cases from highly specialised treatment centres and the Danish Cancer Registry ensured accurate ascertainment with minimal misclassification, and the availability of detailed information on smoking habits, length of education and use of acetaminophen reduced the risk for confounding.

We then assess the minimal misclassification rate over the results of the different variants of classifiers in order to quantify the bias arising when the optimal classification method and/or its tuning parameters are selected a posteriori in a data-driven manner.

We assess the minimal misclassification rate over the different variants of classifiers in order to quantify the bias arising when the optimal classifier is selected a posteriori in a data-driven manner.