Hi. In this video we will learn more about, uh, randomized search.
Randomized search is different from research that instead of testing for all
parameter combinations,
we specify distributions in our parameter grid and randomized search
and randomly samples values from these distributions. Uh, you'll know,
uh, what I mean on this example. Uh, here I define, uh,
three distributions. First is discrete uniform distribution,
generating random integers.
Second is uniform continuous distribution,
and the third one is exponential distribution.
Their parameters in the brackets are minimum and maximum value. Uh, we can, uh,
specify of course any other type of distribution.
Using the r v s method. We randomly sample a value from this distribution.
And when we repeat that, for example, 1000 times, like in this loop,
we can plot then the histogram of this distribution and its shape is now
clearly to see
this way we define our parameter grid, and in the randomized search,
cross validation, uh, we have to specify also, uh,
number of iterations, uh, parameter,
which limits the number of parameter combinations to test other
parameters are same as in grid search. In
our next video, we will learn more about tune search, cross validation.