When reading the slidesa presentation on "expectation propagation"propagation," I found thea strange formula onfor computing $\text{E}[X]$, which is shown in the yellow block of the attached figure. from a conditional probability:
I could not figure out$$\text{E}[X] = \frac{\int x P(y_i|x) dx}{\int P(y_i|x) dx}$$
Can someone please explain how to get this formula was derived? The source is slide 24 in the presentation linked above.
When reading the slides on "expectation propagation", I found the formula on computing $\text{E}[X]$, which is shown in the yellow block of the attached figure.
I could not figure out how to get this formula.
When reading a presentation on "expectation propagation," I found a strange formula for computing $\text{E}[X]$ from a conditional probability:
$$\text{E}[X] = \frac{\int x P(y_i|x) dx}{\int P(y_i|x) dx}$$
Can someone please explain how this formula was derived? The source is slide 24 in the presentation linked above.
whenWhen reading the slides on "expectation propagation", I found the formula on computing E[X]$\text{E}[X]$, which is shown in the yellow block of the attached figure.
I could not figure out how to get this formula?.
when reading the slides on "expectation propagation", I found the formula on computing E[X], which is shown in the yellow block of the attached figure. I could not figure out how to get this formula?
When reading the slides on "expectation propagation", I found the formula on computing $\text{E}[X]$, which is shown in the yellow block of the attached figure.
I could not figure out how to get this formula.
when reading the slides on "expectation propagation", I found the formula on computing E[X], which is shown in the yellow block of the attached figure. I could not figure out how to get this formula?
