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)
“The Englishman’s strong point is his vigorous insularity; that of the American his power of adaptation. Each of these attitudes has its perils. The Englishman stands firmly on his feet, but he who merely does this never advances. The American’s disposition is to step forward even at the risk of a fall.”
—Thomas Wentworth Higginson (1823–1911)