Sentence examples for model evaluation we from inspiring English sources

With respect to model evaluation, we found that the consideration of local sensitivities to simulation quality added valuable information not included in the other evaluation criteria (Nash Sutcliffe efficiency and Peak timing).

In this research, in order to enhance the model evaluation, we use a cross-validation method with k = 10.

To account for the potential bias due to the use of the same dataset for both model construction and model evaluation, we deployed a contextually novel strategy, based on the 0.632+ bootstrap approach [42], [43], to support the statistical validity of the relative accuracy of the classifiers reported in this paper.

For model evaluation we used leave-one-out cross-validation (LOOCV).

To take clustering into account in the model evaluation, we assessed the predictive performance in individual anesthesiologists (within cluster performance).

Based on the experience with duloxetine, and careful model evaluation, we believe that these assumptions are reasonable.

For defining model evaluation parameters, we defined the following terms according to Keramati et al. (2014): True negative (TN) refers to the number of negative tuples that were labeled correctly by the classifier.

Different classes of ncRNAs exhibit different patterns of molecular evolution, making the comparative model evaluation which we have described crucial to designing an effective whole-genome screen.

Our field study also indicated that the single-compartment model was adequate for designing the model evaluation study we had conducted.

While these interactions are empirically determined, at the model evaluation stage we can check that the interactions identified by domain experts are captured.

Furthermore, each CV experiment can be randomly replicated a number of times in order to increase the stability of model evaluation (but we did not do that in the present study).