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As compared with other NR blur metrics, our method yields competitive performance with reasonable complexity.
In Fig. 9, the results show that the proposed method yields competitive results comparing to these four methods.
To assess the reliability of our tool, we also provide in Supplementary Material 3 a study on tumour classification showing that this method yields competitive results with state-of-the-art methods.
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The proposed method yielded competitive results compared to the previously proposed measures with regard to Li's benchmark [13], showing a high correlation with human ratings.
As for the two classification methods, LR yields competitive performance in Examples 1 and 2 and becomes less competitive when logistic models with nonlinear patterns are applied in Examples 3 and 4. The performance of TREE is modest considering the nature of recursive partition.
> It is evident that our proposed methods, linear kernel machine estimation method (LKME) and Gaussian kernel machine estimation method (GKME), yield competitive performance in all examples.
That slow-low method yields uniformly cooked meat, but it takes forever.
But her admittedly unscientific curation method yields a complex and substantial experience.
Our method yields several improvements.
This method yields >95% MNC preparation.
The latter method yields faster running times.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com