Statistical learning theory
Framework for machine learning / From Wikipedia, the free encyclopedia
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This article is about statistical learning in machine learning. For its use in psychology, see Statistical learning in language acquisition.
See also: Computational learning theory
Statistical learning theory is a framework for machine learning drawing from the fields of statistics and functional analysis.[1][2][3] Statistical learning theory deals with the statistical inference 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.