Books
Here is a list of optional books for further background reading.
-
Luc Devroye, László Györfi, Gábor Lugosi.
A probabilistic theory of pattern recognition
.
Springer, 1996.
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Richard O. Duda, Peter E. Hart and David G. Stork.
Pattern classification
.
Wiley, 2001.
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Trevor Hastie, Robert Tibshirani and Jerome Friedman.
The elements of statistical learning: data mining,
inference, and prediction
.
Springer, 2001.
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Michael J. Kearns and Umesh V. Vazirani.
An introduction to computational learning
theory.
MIT Press, 1994.
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Tom M. Mitchell.
Machine learning
.
McGraw-Hill, 1997.
-
Vladimir N. Vapnik.
The nature of statistical learning theory
.
Springer, 1995.
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Vladimir N. Vapnik.
Statistical learning theory
.
Wiley, 1998.