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:
“I can’t make head or tail of Life. Love is a fine thing, Art is a fine thing, Nature is a fine thing; but the average human mind and spirit are confusing beyond measure. Sometimes I think that all our learning is the little learning of the maxim. To laugh at a Roman awe-stricken in a sacred grove is to laugh at something today.”
—Wallace Stevens (1879–1955)
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—Willard Van Orman Quine (b. 1908)