Empirical risk minimization (ERM) is a principle in statistical learning theory which defines a family of learning algorithms and is used to give theoretical bounds on the performance of learning algorithms.
Read more about Empirical Risk Minimization: Background, Empirical Risk Minimization
Famous quotes containing the words empirical and/or risk:
“To develop an empiricist account of science is to depict it as involving a search for truth only about the empirical world, about what is actual and observable.... It must involve throughout a resolute rejection of the demand for an explanation of the regularities in the observable course of nature, by means of truths concerning a reality beyond what is actual and observable, as a demand which plays no role in the scientific enterprise.”
—Bas Van Fraassen (b. 1941)
“It is not a piece of fine feminine Spitalfields silk—but is of the horrible texture of a fabric that should be woven of ships’ cables & hausers. A Polar wind blows through it, & birds of prey hover over it. Warn all gentle fastidious people from so much as peeping into the book—on risk of a lumbago & sciatics.”
—Herman Melville (1819–1891)