Abstract
The theory for controlling the generalization ability of learning machines is devoted to constructing an inductive principle for minimizing the risk functional using a small sample of training instances.
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© 2000 Springer Science+Business Media New York
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Vapnik, V.N. (2000). Controlling the Generalization Ability of Learning Processes. In: The Nature of Statistical Learning Theory. Statistics for Engineering and Information Science. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-3264-1_5
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DOI: https://doi.org/10.1007/978-1-4757-3264-1_5
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-3160-3
Online ISBN: 978-1-4757-3264-1
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