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However, due to the subjective nature of the Twitter datasets, metaheuristic-based clustering methods outperforms the traditional methods for sentiment analysis.
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All methods outperform the traditional rating curve.
Local methods outperform the global methods in terms of energy efficiency.
In the coded configuration, however, the Monte Carlo methods outperform the conventional methods.
Both of the DNN-based feature mapping methods outperform the conventional dereverberation methods.
The proposed methods outperform the conventional MMSE method for all values of ρ.
The proposed methods outperform the "Tubbax" and "Fan+Tubbax" methods in all cases.
In addition, we verify that both proposed methods outperform the equal power allocation method.
The performance analysis shows that these methods outperform the traditional methods.
Considering the overall prediction accuracy for the test set, the RF and RVM methods outperformed the others.
We demonstrate that our methods outperform the previously reported models across the studied datasets.
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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