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On the Rate of Convergence of Local Averaging Plug-In Classification Rules Under a Margin Condition

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2 Author(s)
Kohler, M. ; Saarlandes Univ., Saarbrucken ; Devroye, L.

The rates of convergence of plug-in kernel, partitioning, and nearest neighbors classification rules are analyzed. A margin condition, which measures how quickly the a posteriori probabilities cross the decision boundary, smoothness conditions on the a posteriori probabilities, and boundedness of the feature vector are imposed. The rates of convergence of the plug-in classifiers shown in this paper are faster than previously known

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Information Theory, IEEE Transactions on  (Volume:53 ,  Issue: 5 )