binary classification
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Discriminative Calibration: Check Bayesian
However, SBC has drawbacks: The test statistic is somewhat ad-hoc, interactions are difficult to examine, multiple testing is a challenge, and the resulting p-value is not a divergence metric.
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A Universal Growth Rate for Learning with Smooth Surrogate Losses
We first examine how H -consistency bounds vary across surrogates based on the number of classes.
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0ebcc77dc72360d0eb8e9504c78d38bd-Paper.pdf
As a consequence, empirical risk minimizers generally perform very poorly in extreme regions. It is the purpose of this paper to develop a general framework for classification in the extremes.
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