Open lewisscola opened 3 years ago
Base on my understanding, they are two different things:
normalize_Y
means it will normalize the Y
data before doing optimization. But user will always get dimensional output Y
. Unless you debug into the detailed optimization processes, you will not interactive with the normalized Y
.
Exact_feval
means if your evaluation of the objective function f
is exact. For example,
f_math
has a know mathematical formula, usually extact_feval=True
unless you contaminate the evaluation of f
.f_measure
is some a measurement of some physical quantify like temperature, you should gain inexact f_measure
and thus extact_feval=False
, unless you want to treat the measurement as truth and assume no noise in it.
Hi, I don't know the difference between
Is it means that we only have to set one of the parameters? (for example, if we choose normalize_Y=True, we don't have to set exact_feval=False) Could you help me explain it?
Thank you!
normalize_Y
andexact_feval
in GpyOpt. I see the documention like: