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:
“Research shows clearly that parents who have modeled nurturant, reassuring responses to infants’ fears and distress by soothing words and stroking gentleness have toddlers who already can stroke a crying child’s hair. Toddlers whose special adults model kindliness will even pick up a cookie dropped from a peer’s high chair and return it to the crying peer rather than eat it themselves!”
—Alice Sterling Honig (20th century)
“Judge Ginsburg’s selection should be a model—chosen on merit and not ideology, despite some naysaying, with little advance publicity. Her treatment could begin to overturn a terrible precedent: that is, that the most terrifying sentence among the accomplished in America has become, “Honey—the White House is on the phone.””
—Anna Quindlen (b. 1952)