Hey there, a newbie aboard! Great question! Model retraining can mean different things depending on the context, but in general, it refers to updating an existing model using new data. So, your understanding is partially correct! When you retrain a model, you typically use the same model architecture and parameters as before, but update the model's weights (or coefficients) based on new data. In this way, the model can improve its accuracy and generalizability as it learns from more examples. As for SAS Model Studio specifically, I'm not 100% sure, but based on my experience with other machine learning tools, I would expect that it updates the existing model's weights rather than generating a completely new model. However, if there are new variables or features in the data that were not included in the original model, you may need to modify the model architecture to account for these changes. Hope that helps! Let me know if you have any more questions.
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