Model Selection Task

Context:
- It can be solved by a Model Selection System (that implements a model selection algorithm).
Example(s):
- a Statistical Model Selection Task / Machine Learning Model Selection Task, which can range from being a Classification Model Selection Task to being a Ranking Model Selection Task to being a Estimation Model Selection Task.
- …
Counter-Example(s):
- a Model Evaluation Task.
See: Statistical Model, Design of Experiments, Hyperparameter Tuning.

References

(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.