MDL, or Minimum Description Length, is a principle in information theory that suggests the best model for a given data set is the one that minimizes the total length of the encoded data and the length of the model description. This principle provides a formal framework for model selection, balancing the trade-off between model complexity and goodness of fit to the data. Essentially, it emphasizes that simpler models are preferred if they can adequately describe the data.
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