Information criteria are statistical tools used to evaluate and compare the goodness of fit of different models, balancing model complexity with the ability to explain the data. They provide a quantitative measure for selecting models, helping to identify which one best captures the underlying patterns without overfitting. This concept plays a vital role in prediction and model evaluation, particularly when using advanced computational frameworks.
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