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
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“‘Tis very certain that each man carries in his eye the exact indication of his rank in the immense scale of men, and we are always learning to read it. A complete man should need no auxiliaries to his personal presence.”
—Ralph Waldo Emerson (1803–1882)
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