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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.
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