Model Selection Task

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A Model Selection Task is a selection task of some mathematical model from a class of mathematical models.



References

2020

  • (Wikipedia, 2020) ⇒ https://en.wikipedia.org/wiki/model_selection Retrieved:2020-6-5.
    • Model selection is the task of selecting a statistical model from a set of candidate models, given data. In the simplest cases, a pre-existing set of data is considered. However, the task can also involve the design of experiments such that the data collected is well-suited to the problem of model selection. Given candidate models of similar predictive or explanatory power, the simplest model is most likely to be the best choice (Occam's razor).

      Konishi & Kitagawa (2008, p. 75) state, "The majority of the problems in statistical inference can be considered to be problems related to statistical modeling". Relatedly, has said, "How [the] translation from subject-matter problem to statistical model is done is often the most critical part of an analysis".

      Model selection may also refer to the problem of selecting a few representative models from a large set of computational models for the purpose of decision making or optimization under uncertainty.


2011

2009