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I'm wondering is there a good stopping condition that people usually use to decide convergence? Suppose I hope to find the function inputs that give me a function value that is allowed to differ from the optimal value by 10%. Is there a way to do that?
If that is impossible, what's the rule of thumb way of deciding how long to run Spearmint for?
Thank you very much!
The text was updated successfully, but these errors were encountered:
Hi do you have any updates or ideas for this question? I am also wondering that. For a model with a few hyper-parameters to optimization, it's almost impossible to arrive at a convergence as the simple demo shows. The good news is that it truly works and gets fairly good results just after a few iterations, although it could be fluctuating a lot.
I'm wondering is there a good stopping condition that people usually use to decide convergence? Suppose I hope to find the function inputs that give me a function value that is allowed to differ from the optimal value by 10%. Is there a way to do that?
If that is impossible, what's the rule of thumb way of deciding how long to run Spearmint for?
Thank you very much!
The text was updated successfully, but these errors were encountered: