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:
“Without our being especially conscious of the transition, the word “parent” has gradually come to be used as much as a verb as a noun. Whereas we formerly thought mainly about “being a parent,” we now find ourselves talking about learning how “to parent.” . . . It suggests that we may now be concentrating on action rather than status, on what we do rather than what or who we are.”
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smiling carves dreams, bright cells
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