Abstract
In this section, we define the mathematical model and introduce the notation we will use for the entire book. Let (X, Y) be a pair of random variables taking their respective values from R d and {0, 1}. The random pair (X, Y) may be described in a variety of ways: for example, it is defined by the pair (μ, η), where μ is the probability measure for X and μ is the regression of Y on X. More precisely, for a Borel-measurable set A ⊆ R d,
and for any x ∈ R d,
.
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© 1996 Springer Science+Business Media New York
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Devroye, L., Györfi, L., Lugosi, G. (1996). The Bayes Error. In: A Probabilistic Theory of Pattern Recognition. Stochastic Modelling and Applied Probability, vol 31. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-0711-5_2
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DOI: https://doi.org/10.1007/978-1-4612-0711-5_2
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4612-6877-2
Online ISBN: 978-1-4612-0711-5
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