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)
“Men’s hearts are cold. They are indifferent. Not all the coal that is dug warms the world. It remains indifferent to the lives of those who risk their life and health down in the blackness of the earth; who crawl through dark, choking crevices with only a bit of lamp on their caps to light their silent way; whose backs are bent with toil, whose very bones ache, whose happiness is sleep, and whose peace is death.”
—Mother Jones (1830–1930)