What I am trying to do :
I am trying to apply a bayesian hyperband sweep.
Now as mentioned in the docs, under early terminate we have to mention 4 params (generally), those are min_iter, s, eta and max_iter, it would look something like follows.
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My doubts summarized:
In summary, what I want to know,
Given all 4 : min_iter, s, eta, and max_iter

at which epochs will the hyperband algorithm check for improvement??

considering I am trying to do bayesian hyperband, how many runs will be evaluated in the first bracket, and how many runs will be evaluated in the consecutive brackets?

is there any way or rule(s) of thumb to decide what values are good to take for these 4 parameters(min_iter, s, eta, and max_iter) ?

please explain about the paramters s and eta (especially eta) in a bit more detail, i.e. with a bit or underlying maths (please keep it simple if possible).
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What is my doubt about?? (explained in a bit more detail/context):
in the docs it is only somewhat explained that at which epochs (their) implementation of the hyperband algorithm checks for improvement and takes decision whether to terminate a run or not.
 When only the minimum number of iterations for each run are our concern
early_terminate:
type: hyperband
min_iter: 3
The brackets for this example are: [3, 3*eta, 3*eta*eta, 3*eta*eta*eta]
, which equals [3, 9, 27, 81]
.
 When only the maximum number of iterations for each run are our concern
early_terminate:
type: hyperband
max_iter: 27
s: 2
The brackets for this example are [27/eta, 27/eta/eta]
, which equals [9, 3]
.
But what about a case when both the minimum and maximum number of iterations for each run are our concern??
Like the one as follows…
early_terminate:
type: hyperband
min_iter: 10
s: 3
eta: 4
max_iter: 50