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Use this tag for any use of optimization within statistics.

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Tuning skopt to minimise correctly

of running the model (~1 to 20s), and the number of instances to fit, and the fact that my error function must be evaluated numerically (so no analytic derivative function) I was looking at Bayesian optimization … I have already tried increasing the number of random samples to initiate the optimizer, and initiating with a 5 by 5 uniform grid of samples (I can't sample much finer without making the optimization process …
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