# Classification via local multi-resolution projections

@article{Monnier2011ClassificationVL,
title={Classification via local multi-resolution projections},
author={Jean-Baptiste Monnier},
journal={arXiv: Statistics Theory},
year={2011}
}
We focus on the supervised binary classification problem, which consists in guessing the label $Y$ associated to a co-variate $X \in \R^d$, given a set of $n$ independent and identically distributed co-variates and associated labels $(X_i,Y_i)$. We assume that the law of the random vector $(X,Y)$ is unknown and the marginal law of $X$ admits a density supported on a set $\A$. In the particular case of plug-in classifiers, solving the classification problem boils down to the estimation of the…
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