Saying a model has a good fit means its predictions closely match the actual observed values in the dataset. Fit (or goodness-of-fit) is a measure of how well the model represents the underlying data distribution. Merely finishing training without errors, standardizing feature scales, or minimizing the number of parameters do not, by themselves, describe the quality of fit.
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