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Bayes Decisions in a
Neural Network-PAC Setting |
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Abstract. In this paper, we investigate the problem of automatic
object classification. We assume that each object is represented by a feature
vector \bar {x} and belongs to one of finitely many possible object-types
T0,...,Tr. Given an object with feature vector
\bar {x}, we want to decide to which type it belongs. This decision
is, in general, not error-free because objects of different types may occasionally
have the same feature vector. Let P(\bar {x}
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