Sentence examples for evaluating the predictive accuracy from inspiring English sources

The ROC curves are significant for evaluating the predictive accuracy of a chosen model particularly in dichotomous statistical modeling such as logistic regression (Gorsevski et al. 2006), and the area under the curve obtained from the ROC (receiver operating characteristics) plot is the most preferred and applicable type of statistical assessment (Akgun et al. 2012).

We started by evaluating the predictive accuracy of the KronRLS model under each of the settings S1 S4.

Interestingly, we found only a 34% overlap in reactions collected from the three databases--highlighting the importance of evaluating the predictive accuracy of the resulting genome-scale model.

Cross validation, which usually gives lower predictive values than those obtained on the learning sets, is the recommended way of evaluating the predictive accuracy of a given marker at the individual level.

Wrapper methods consist of three components: a search algorithm for systematically traversing through the space of all possible feature subsets, a scoring function for evaluating the predictive accuracy of the feature subsets, and the learning algorithm around which the feature selection procedure is wrapped [ 34].

Therefore, care must be taken when evaluating the predictive accuracy of genetic models as they often perform better in the populations in which they are developed, and the performance of a model can be affected by differences in populations, genotype frequencies, phenotypic effect sizes and disease incidence.

To evaluate the predictive accuracy of different methodologies for selecting a basal FSH threshold level that prognosticates live birth after IVF.

To quantitatively evaluate the predictive accuracy of the equation of the state, we compared numerical calculation results with reference experimental data.

In this study, we evaluated the predictive accuracy of ED triage by nurses applying ESI using a novel approach that leveraged both clinical judgment of a treating physician with knowledge of actual ED resource utilization and clinical outcome data captured from the EHR.

We also constructed linear SVM classifiers on the mapped informative clusters to evaluate the predictive accuracy.

The test data set was then used to evaluate the predictive accuracy of the classifier constructed from the training data set.