Displaying similar documents to “Probabilities of discrepancy between minima of cross-validation, Vapnik bounds and true risks”

Theory of classification : a survey of some recent advances

Stéphane Boucheron, Olivier Bousquet, Gábor Lugosi (2005)

ESAIM: Probability and Statistics

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The last few years have witnessed important new developments in the theory and practice of pattern classification. We intend to survey some of the main new ideas that have led to these recent results.

On the Optimality of Sample-Based Estimates of the Expectation of the Empirical Minimizer

Peter L. Bartlett, Shahar Mendelson, Petra Philips (2010)

ESAIM: Probability and Statistics

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We study sample-based estimates of the expectation of the function produced by the empirical minimization algorithm. We investigate the extent to which one can estimate the rate of convergence of the empirical minimizer in a data dependent manner. We establish three main results. First, we provide an algorithm that upper bounds the expectation of the empirical minimizer in a completely data-dependent manner. This bound is based on a structural result due to Bartlett and Mendelson, which...

A simple upper bound to the Bayes error probability for feature selection

Lorenzo Bruzzone, Sebastiano B. Serpico (1998)

Kybernetika

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In this paper, feature selection in multiclass cases for classification of remote-sensing images is addressed. A criterion based on a simple upper bound to the error probability of the Bayes classifier for the minimum error is proposed. This criterion has the advantage of selecting features having a link with the error probability with a low computational load. Experiments have been carried out in order to compare the performances provided by the proposed criterion with the ones of some...