Concept

Minimum description length

Summary
Minimum Description Length (MDL) is a model selection principle where the shortest description of the data is the best model. MDL methods learn through a data compression perspective and are sometimes described as mathematical applications of Occam's razor. The MDL principle can be extended to other forms of inductive inference and learning, for example to estimation and sequential prediction, without explicitly identifying a single model of the data. MDL has its origins mostly in information theory and has been further developed within the general fields of statistics, theoretical computer science and machine learning, and more narrowly computational learning theory. Historically, there are different, yet interrelated, usages of the definite noun phrase "the minimum description length principle" that vary in what is meant by description:
  • Within Jorma Rissanen's theory of learning, a central concept of information theory, models are statistical hypotheses and descriptions are defi
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