It is very useful to have nicely formatted equations in blog posts. The test example below uses the MathJax JavaScript library, with a ruhoh configuration based on a GitHub comment from Ramnath Vaidyanathan.

Loss functions and empirical risk

Given a dataset of observed input-output pairs $(x_1, y_1), \ldots, (x_N, y_N)$, we can estimate a function $f(x)$ to predict future values of $y$ given $x$. We measure the difference between the true $y$ and our prediction $f(x)$ with a loss function, such as $\ell(y, f(x)) = (y-f(x))^2$. We can then compute the empirical risk $R$ of our function $f$ with respect to loss function $\ell$ over a dataset as: $$ R(\ell,f) = \frac{1}{N} \sum_{i=1}^{N} (y_i - f(x_i))^2 $$

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Published

2012-08-19

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