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The phrase "a more robust model" is correct and usable in written English.
It can be used when discussing improvements or enhancements to a model, particularly in contexts like data analysis, machine learning, or scientific research.
Example: "After several iterations, we have developed a more robust model that can better predict outcomes."
Alternatives: "a stronger model" or "a more resilient model".
Exact(27)
It must be phased out as existing contracts come to their end and gradually replaced by a more robust model for all schools, such as that of the maintained trust school introduced by the Labour government in 2006.
Therefore, the new model is found to be a more robust model in comparison to Altman's, Ohlson's and Zmijewski's models.
To estimate scores accurately, a support vector regression (SVR) technique was introduced as a more robust model.
The result is a more robust model for the productivity of fibers by free surface electrospinning from a wire electrode.
The tools used in machining vary in shapes and design hence a more robust model is required to include these varieties.
This thus creates a more robust model because adding more of these binary classifiers which increases the stability and informative ability of the subspace co-projection when faced with a multi-class scenario.
Similar(33)
The specification of appropriate monotonicity constraints allows for an optimal combination of flexibility and expert knowledge to guarantee for a more robust modelling.
Finally, Artificial Neural Networks (ANN) models were developed to allow for a more robust simulation model to be built and comparison between ANN and RSM models to be performed.
The goal of this review is to use these three domains of diversity deficit to evaluate existing models, with a longer term goal of creating a more robust framework for assessing landscape models in the future.
It is then safe to conclude that SVMs alone are not able to perform a good optimization, and by combining with a variable selection step we can obtain a minimum subset of important variables to train a faster and more robust model, yielding better prediction performance.
This approach can yield a simplified and more robust model.
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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