TL;DRAbstract
Different rules for the problem of classifying one (or more) unit to one of several distinct populations on the basis of random training samples are considered and their asymptotic probabilities of misclassification (PMC) are derived.
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Different rules for the problem of classifying one (or more) unit to one of several distinct populations on the basis of random training samples are considered and their asymptotic probabilities of misclassification (PMC) are derived.
Keywords
Basis (linear algebra)MathematicsArtificial intelligenceUnit (ring theory)Computer sciencePattern recognition (psychology)Machine learning
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