Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: AUC: Nonparametric Estimators and Their Smoothness   Nonparametric estimation of a statistic, in general, and of the error rate of
a classification rule, in particular, from just one available dataset through
resampling is well mathematically founded in the literature using several
versions of bootstrap and influence function. This article first provides a
concise review of this literature to establish the theoretical framework that
we use to construct, in a single coherent framework, nonparametric estimators
of the AUC (a two-sample statistic) other than the error rate (a one-sample
statistic). In addition, the smoothness of some of these estimators is well
investigated and explained. Our experiments show that the behavior of the
designed AUC estimators confirms the findings of the literature for the
behavior of error rate estimators in many aspects including: the weak
correlation between the bootstrap-based estimators and the true conditional
AUC; and the comparable accuracy of the different versions of the bootstrap
estimators in terms of the RMS with little superiority of the .632+ bootstrap
estimator.

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The categories of this paper are: alg-geom
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The categories of this paper are: solv-int
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The categories of this paper are: chem-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: plasm-ph
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The categories of this paper are: hep-lat
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The categories of this paper are: dg-ga
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The categories of this paper are: gr-qc
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The categories of this paper are: q-alg
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The categories of this paper are: nlin
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The categories of this paper are: adap-org
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The categories of this paper are: physics
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The categories of this paper are: astro-ph
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The categories of this paper are: q-fin
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The categories of this paper are: math-ph
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The categories of this paper are: ao-sci