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Statistical learning theory

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Statistical learning theory is a framework for machine learning drawing from the fields of statistics and functional analysis. 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.

Statistical learning theory - Wikipedia Jump to content From Wikipedia, the free encyclopedia Framework for machine learning 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 Part of a series on Machine learning and data mining Paradigms Supervised learning Unsupervised learning Semi-supervised learning Self-supervised learning Reinforcement learning Meta-learning Online learning Batch learning Curriculum learning Rule-based learning Neuro-symbolic AI Neuromorphic

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