The Bayesian Information Criterion (BIC) is a statistical tool used for model selection among a finite set of models. It helps to identify the best-fitting model while penalizing for the number of parameters to avoid overfitting. The BIC balances the goodness of fit of the model against its complexity, providing a way to compare different models based on their likelihood and the number of parameters used.
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