The Bayesian Information Criterion (BIC) is a statistical metric for model selection among a finite set of models; it balances the likelihood of the model against the complexity by imposing a penalty for the number of parameters. BIC is particularly effective when dealing with large datasets, as it asymptotically selects the true model as the dataset size grows, assuming that the true model is among the candidate models.
Relevant Degrees
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