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The phrase "assess model" is correct and usable in written English.
It can be used when discussing the evaluation or analysis of a particular model, often in contexts like research, data analysis, or machine learning.
Example: "In order to improve our predictions, we need to assess the model's performance against the test data."
Alternatives: "evaluate the model" or "analyze the model".
Exact(60)
In addition to prediction assessment, CASP provides a platform to develop and assess model evaluation methods.
Bayes factors were used to assess model fit.
Cross-validation was performed to assess model accuracy.
When evaluating prediction models, test set data are typically used to assess model performance with unknowns.
For this reason, NFI is no longer used to assess model fit (Bentler 1990; Hoyle 2011).
In addition, root mean square of residual (RMSR) can be obtained to assess model fit.
Cost-benefits analysis could also be performed to assess model components and operational success.
Finally, to assess model significance and to rule-out chance correlation, Y-randomization procedure was applied to all models.
The Hosmer-Lemeshow test, along with the examination of residuals, was used to assess model goodness of fit.
For this reason, several widely used descriptive goodness-of-fit indices were used to assess model fit.
A more impartial way is to assess model quality by comprehensible measures like accuracy, clarity, completeness, conciseness, or consistency.
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