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.
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)
“I saw the man my friend ... wants pardoned, Thomas Flinton. He is a bright, good-looking fellow.... Of his innocence all are confident. The governor strikes me as a man seeking popularity, who lacks the independence and manhood to do right at the risk of losing popularity. Afraid of what will be said. He is prejudiced against the Irish and Democrats.”
—Rutherford Birchard Hayes (18221893)