Sentence examples for classification was estimated from inspiring English sources

By superimposing the vector-based delineation map on the grid-based map, the IAR of each grid-based land use classification was estimated with very little uncertainty, after calculating the IARs of all grid cells in the entire urban watershed.

The conversion factor considering the change in ICD classification was estimated to 0.57 (95% CI 0.56 0.58) in the seasonal model.

The performance of the classification was estimated using standard measures.

Agreement between the reference standard and the automated coded classification was estimated using the Kappa statistic.

The unbiased diagnostic accuracy (proportion of correct classification) was estimated to 91.24 %, against 92.65 % initially computed on the original dataset.

After correcting the originally misclassified pairs with DNA-based zygosinformationtion, correct classification was estimated to be 98.0%.

However, so far IAR of each classification is estimated very roughly and applied in the corresponding hydrologic models almost empirically.

Another possible explanation is that the percentages used for craniofacial classification were estimated in populations from Europe [ 12, 32], where the Caucasian race is most predominant and exhibits morphological features different from ours (in Colombia, and mainly in Antioquia, where a mixed race prevails).

The 6-item short version was selected on the basis of sequential logistic regression, to optimize concordance with the clinical classification; and was estimated to have a sensitivity of 68.7% and specificity of 99.5% with total classification accuracy of 97.9%, evaluated using population survey data [ 216].

Classification accuracy was estimated through confusion matrixes and uncertainty in terms of both membership probability and confusion indices.

The classification accuracy was estimated using the leave-one-out method which is known to provide a least bias estimate [51].