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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.

^ Vapnik, Vladimir N. (1995). The Nature of Statistical Learning Theory. New York: Springer. ISBN 978-1-475-72440-0.
^ Hastie, Trevor; Tibshirani, Robert; Friedman, Jerome H. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer Series in Statistics. New York, NY: Springer. ISBN 978-0-387-84857-0.
^ Mohri, Mehryar; Rostamizadeh, Afshin; Talwalkar, Ameet (2012). Foundations of Machine Learning. US, Massachusetts: MIT Press. ISBN 9780262018258.