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The D-optimal design yielded quadratic models with excellent fit and predictive power for the responses water flux through the membrane, and the enrichment factor towards water.
The GFA and LSSVM models were performed the rigorous internal and external validation, further verifying these models with excellent robustness and predictive ability.
On the other hand, it is easy to construct complex models with excellent or even perfect fit, which are mechanistically meaningless and do not generalize (i.e., "over-fitting").
We report un-weighted multilevel binary logistic regression models with excellent SRH as the reference category.
In Cohort 2, both the Elixhauser index (c = 0.87; 95% CI: 0.84, 0.90) and Charlson index (c = 0.82; 95% CI: 0.79, 0.86) resulted in full models with excellent predictive performance.
At the other extreme of putting very little weight on the fit to the density, models with excellent geometry but higher R factors and lower FSCs were obtained, and practically no differences between FSCwork and FSCtest were observed.
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It is observed that the data can be satisfactorily fitted using Tòth model with excellent fitting accuracy around 2.2% within the experimental range.
Our study reveals that highly parameterized geostatistical models perform the best among the models compared, while the zonation model with excellent knowledge of stratigraphy also yields comparable results.
An improved structure mechanical modeling with excellent accuracy is developed for single-cell thin-walled closed-section composite beams based on previous work.
The procedure results in a constrained polynomial model with excellent descriptive and interpolating features in comparison with an extended Ratkowsky-type model and classical polynomial model, by combining specific properties of both model types.
The LROLS algorithm alone is capable of producing a very parsimonious model with excellent generalisation performance while the D-optimality design criterion further enhances the model efficiency and robustness.
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