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When engineering the multistatic tracking system, sensitivity studies help to tune model assumptions and approximations.
These kinds of studies can result in non-trivial workflows due to nested cross-validation and parameter sweeps needed to properly tune model parameters and evaluate model performance.
The training set was then used to develop SVM models and the test set was used to fine tune model parameters and assess their predictive performance.
The feasibility of this approach is established by thermodynamic modeling and the construction of a proof-of-concept prototype, which is also used to fine tune model parameters.
To tune model parameters we used evidence from independent studies.
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Using the workers on its platform, DefinedCrowd can augment existing datasets with new specialized data that can help tune models for specific applications.
"Ordinarily, optimizing a machine learning model for multiple hardware platforms is difficult because developers need to tune models manually for each platform's hardware and software configuration," AWS's Sukwon Kim and Vin Sharma write in today's announcement.
The proposed procedure provides an accurate, reliable and easy-to-tune model of photovoltaic array.
Section 3 describes the tuning model for adaptive computations.
In such cases, our tuning model allows an AC to specify a pinnedLevel S i (i∈[0,3]).
In this article, we propose a tuning model for adaptive computations.
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