the robustness of the model for predicting vs ensured the robustness of the

Both phrases are correct, but they are used in different contexts. 'The robustness of the model for predicting' is used when discussing the strength and reliability of a specific model in making predictions. 'Ensured the robustness of the' is used when emphasizing the act of guaranteeing the strength and reliability of something without specifying a particular model or prediction.

Last updated: March 17, 2024 • 724 views

This phrase is correct and commonly used in the context of discussing the strength and reliability of a specific model for making predictions.

"the robustness of the model for predicting"

This phrase is used when referring to the ability of a particular model to make accurate predictions consistently. It highlights the robustness of that specific model in the context of prediction.

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These performance metrics have been used in a number of studies and ensures an effective means of deciding the robustness of the model for predicting daily.

This phrase is correct and commonly used when emphasizing the act of guaranteeing the strength and reliability of something without specifying a particular model or prediction.

"ensured the robustness of the"

This phrase is used to highlight the action of ensuring the strength and reliability of something, without specifying the exact nature of what is being made robust. It is a more general statement compared to the first phrase.

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The Freetune program ensured the robustness of the calibration. With it, no re- calibration or calibration fine-tuning was required. The system automatically ...
Jun 4, 2015 ... ... data collection methods that ensured the robustness of the Index's results and will put the data collected on Georgia in the regional context.
Mar 11, 2014 ... ... 10−8 has served the genetics community well and has ensured the robustness of the majority of GWAS findings. Single-variant testing across ...
Apr 14, 2014 ... It also ensured the robustness of the proposed method against different initial values for noise and heterogeneity, even when the target number ...

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the robustness of the model for predicting vs ensured the robustness of the