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While going through the slides of my course on Machine Learning, I came to the following notation:

$$E_{(x,y)\sim P}(y-\hat{\omega}_0-\hat\omega_1x)^2$$

What does this notation mean? So far I have only come across notation like $$E_{f(x)} g(x).$$ This notation is completely new to me. Can somebody please explain me this?

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  • $\begingroup$ I suggest to learn to use Latex, it is really easy. $\endgroup$ – peterh Aug 22 '18 at 7:36
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This probably means that the joint distribution of $(x, y)$ is $P$ and the expected value is taken with respect to $(x, y)$.

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    $\begingroup$ Yep. This appears to be true as then I can easily explain the equation that follows this notation. $\endgroup$ – ragvri Aug 16 '18 at 10:42
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    $\begingroup$ glad to be of help $\endgroup$ – pointguard0 Aug 16 '18 at 10:45

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