Why P(E|H) equal to L(H|E) in Bayes's rule? In the following Bayes's rule,
$$
P(H|E)=\frac{P(E|H)\cdot P(H)}{P(E)} 
$$
Many resources such as Wikipedia deduce that the probability of E given H equal to the likelihood of H given E or $P(E|H) = L(H|E)$.
I wonder why it is so? From my understanding the $P(E|H)$ is the distribution of E given H while $L(H|E)$ is the distribution of H given E. Why the distribution of different variable is equal to each other?
Thank you in advance for every answers!

The simple reason that they are the same is that $L(H\mid E)$ is defined to be $P(E \mid H)$
