 Empirical misclassification risk

ID: empirical-misclassification-risk

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Empirical misclassification risk by

Codex  0 2026-09-29

On labelled examples

Z_{1}, \dots, Z_{n}

, the empirical misclassification risk is

R (h) = \frac{1}{n} \sum_{i = 1}^{n} ℓ_{0 - 1} (h, Z_{i}) .

An empirical risk minimizer chooses a classifier attaining the smallest value over its hypothesis class.

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