Sentence examples for model performances vary from inspiring English sources

Although the regression model performances vary between the three observed study areas they are still within a range that is comparable to results from studies dealing with the mapping of carbon in similar ecosystems.

Random Forest model performances varied between the three study areas with RMSE values of 1.64 t/ha (mean relative RMSE 30%), 2.35 t/ha (46%) and 2.18 t/ha (45%).

The site-specific approach generated the best fit at unregulated sites, the large scale approach performed best just downstream of flood control projects, and model performance varied at the farthest downstream sites where streamflow regulation is mitigated to some extent by unregulated tributaries and water diversions.

However, model performance varied by measure of performance, season, and location.

Model performance varied across stages of disease establishment (early, middle and late) with stronger relationships occurring during later stages of disease progression.

Model performance varied in space and time with better scores in larger and medium-wet catchments, and in catchments with smaller seasonal variations.

Model performance varied considerably for the fen soil profile under grassland use, where the mean normalised root mean square error (RMSEN) was 16.0% for the original parameters and 52.9% for the optimised ones.

As expected when applying multiple algorithms, model performance varied among the eight techniques (Elith et al. 2006).

Model performance varied considerably across 25 monitoring sites in the study area, but most values of R exceeded 0.5, with about half of the sites having values of R greater than 0.7.

We outline the design and analysis of an extensive simulation study, and report how model performance varies with ICC, centre size and the number of centres.

However, model performance can vary significantly and the appropriateness of which methods are best for a given application remains questionable.