Statistical learning theory is a framework for machine learning drawing from the fields of statistics and functional analysis. Statistical learning theory deals with the problem of finding a predictive function based on data. Statistical learning theory has led to successful applications in fields such as computer vision, speech recognition, and bioinformatics. It is the theoretical framework underlying support vector machines.
Read more about Statistical Learning Theory: Introduction, Formal Description, Loss Functions, Regularization
Famous quotes containing the words learning and/or theory:
“To raise a son without learning is raising an ass; to raise a daughter without learning is raising a pig.”
—Chinese proverb.
“A theory if you hold it hard enough
And long enough gets rated as a creed....”
—Robert Frost (1874–1963)