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:
“Learning without thinking is labor lost; thinking without learning is dangerous.”
—Chinese proverb.
“The theory seems to be that so long as a man is a failure he is one of God’s chillun, but that as soon as he has any luck he owes it to the Devil.”
—H.L. (Henry Lewis)