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 correct.
Read more about Model Selection: Introduction, Methods For Choosing The Set of Candidate Models, Experiments For Choosing The Set of Candidate Models, Criteria For Model Selection
Famous quotes containing the words model and/or selection:
“It has to be acknowledged that in capitalist society, with its herds of hippies, originality has become a sort of fringe benefit, a mere convention, accepted obsolescence, the Beatnik model being turned in for the Hippie model, as though strangely obedient to capitalist laws of marketing.”
—Mary McCarthy (1912–1989)
“When you consider the radiance, that it does not withhold
itself but pours its abundance without selection into every
nook and cranny”
—Archie Randolph Ammons (b. 1926)