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The binary regression functions are the conditional class probabilitiesUnder zero-one loss, the Bayes classifier iswith arbitrary tie breaking. Its Bayes decision boundary is

The conditional class probability is $p_k(x)=\mathbb{P}(Y=k\mid X=x)$. A Bayes classifier choosesand its Bayes risk isA sequence of classifiers is consistent when $R(h_n)\to R_{\mathrm{Bayes}}$ as $n\to \infty$, with convergence interpreted in probability or in expectation according to whether the training sample is conditioned upon.