BayesSearchCV 参数

Question

I just read about Bayesian optimization and I want to try it.我刚刚阅读了有关Bayesian optimization的信息，我想尝试一下。

I installed scikit-optimize and checked the API, and I'm confused:我安装了scikit-optimize并检查了 API，我很困惑：

I read that Bayesian optimization starts with some initialize samples.我读到贝叶斯优化从一些初始化样本开始。
- I can't see where I can change this number?我看不到在哪里可以更改此号码？ ( BayesSearchCV ) ( BayesSearchCV )
- n_points will change the number of parameter settings to sample in parallel and n_iter is the number of iterations (and if I'm not wrong the iterations can't run in parallel, the algorithm improve the parameters after every iteration) n_points将更改参数设置的数量以并行采样，而n_iter是迭代次数（如果我没记错的话迭代不能并行运行，算法会在每次迭代后改进参数）
I read that we can use different acquisition functions.我读到我们可以使用不同的采集功能。 I can't see where I can change the acquisition function in BayesSearchCV ?我看不到哪里可以更改 BayesSearchCV 中的采集BayesSearchCV ？

Answer 1

Is this something you are looking for?这是你要找的东西吗？

BayesSearchCV(..., optimizer_kwargs={'n_initial_points': 20, 'acq_func': 'gp_hedge'}, ...)

skopt.Optimizer is the one actually doing the hyperparameter optimization. skopt.Optimizer是实际进行超参数优化的那个。

BayesSearchCV will build Optimzier with optimizer_kwargs parameters. BayesSearchCV将使用optimizer_kwargs参数构建Optimzier 。