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)
“Combining paid employment with marriage and motherhood creates safeguards for emotional well-being. Nothing is certain in life, but generally the chances of happiness are greater if one has multiple areas of interest and involvement. To juggle is to diminish the risk of depression, anxiety, and unhappiness.”
—Faye J. Crosby (20th century)