Sentence examples for better model performance than from inspiring English sources

The model based on a local vegetation layer generally exhibited better model performance than the model based on the more generic regional layer.

We find that the most informative indicators of performance are based on social ties and that network indicators result in better model performance than individual characteristics (including both personality and class attendance).

Moreover, GWR models have better model performance than OLS models with the same independent variable, as is indicated by lower AICc values, higher Adjusted R2 values from GWR and the reduction of the spatial autocorrelation of residuals.

The results show that all these three methods have better model performances than the expert screening in terms of R2, the number of variables in the model, and PRESS.

In our real data simulations, the partial prediction models gave slightly better model performance measures than the multiple imputation methods.

For catchments with low moisture homogeneity (IM < 80%), IM is a better predictor of model performance improvement than ITV; whereas for catchments with high moisture homogeneity (IM > 80%), ITV is a better predictor of performance improvement than IM.

Regardless of the approach used, the sensitivity, specificity, positive predictive value and negative predictive value were usually adopted to evaluate the performance of the model, and it is found that alternative identification approaches all had model performance better than that with the ICD-9-CM-based model.

From the results, Pinching4 model showed better performance than Saws model in accounting for rapid degradation of reloading stiffness and unloading stiffness of the bracket connection.

As judging by the sum of weighted residual squares value, Model 1 had better predictive performance than Model 2 and provided estimates closer to observed Cmax and AUC values at doses ranging from 0.3 to 8.0 mg/m (comparable with 0.6 16 mg, Figure 4 ).

Moreover, while the Gaussian model shows better performance than the Laplacian model in the low SNR condition with SNR = -5 dB, both the models in general give comparable performance in the high SNR condition with SNR = 25 dB. Figure 5 RMSE versus different number of microphones for the two noise conditions.

The current UMC2013 model showed better performance than the previous model of Iwata et al. (2008).