Abstract
The goal of this part of the theory is to describe the conceptual model for learning processes that are based on the empirical risk minimization inductive principle. This part of the theory has to explain when a learning machine that minimizes empirical risk can achieve a small value of actual risk (can generalize) and when it cannot. In other words, the goal of this part is to describe necessary and sufficient conditions for the consistency of learning processes that minimize the empirical risk.
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© 2000 Springer Science+Business Media New York
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Vapnik, V.N. (2000). Consistency 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_3
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DOI: https://doi.org/10.1007/978-1-4757-3264-1_3
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-3160-3
Online ISBN: 978-1-4757-3264-1
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