The phrase "a model that performs" is correct and usable in written English.
It can be used when discussing the functionality or effectiveness of a model in various contexts, such as machine learning, statistics, or any performance-related evaluation.
Example: "We need to evaluate a model that performs well under different conditions to ensure its reliability."
Alternatives: "a model that operates" or "a model that functions".
Given the diversity of patient populations and the heterogeneity seen in the meta-analyses of PSI and CURB-65, there is no guarantee that a model that performs well in one setting will do equally well in a different setting.
Intelligence awareness target as a service (IAT) is a model that performs intelligent situational awareness data processing at the level of things [31].
An ideal observer is a model that performs a given task in an optimal way, limited only by the information available and explicitly specified constraints [16].
In this work, we propose to use a model that performs the joint learning to recognize event triggers and protein names simultaneously.
Common mistakes are using a role model with whom people identify poorly (often overlooked when celebrities are used), that performs the right behaviour but is not rewarded in any way (violating the third parameter), or using a model that performs the target behaviour without any problems (violating the fourth parameter).
25 A recent study has mapped Read codes from a UK general practice database to the relevant Charlson comorbid disease groups, resulting in a model that performed well in the prediction of 5-year mortality.
We show, however, that the observed data can be explained by a hierarchical Bayesian model that performs structure learning.
In this article, we analyse the relationship of the motion vector difference and the number of slice groups to develop a new header bits model that performs well when FMO is enabled.
However, in this case there is also the complication that the model that performs worst, yields better mutual information.
With recently collected data and modern statistical methods, we developed a prediction model that performed well in estimating the probability of coronary artery disease.
This situation could be addressed by making a business case with the help of an economic model that perform cost-benefit analysis about the adoption of an RA (Reifer [2002]).
