How bayesopt find kernel parameters

6 次查看（过去 30 天）
Aep
Aep 2020-9-4
编辑： Mahdi Nobar 2021-12-4
Hello all,
I know that bayesopt uses fitrgp to create gaussian process in each iteration. But how bayesopt find the optimize kernel parameters of the Gaussian process regression in each step? Does it optimize kernel parameters at all? If not, what are the kernel paramters being used in each iteration?
I want to know the default configurations of bayesopt for the items above, I was not able to find my answer in the documentation.
Thank you in advance

请先登录，再回答此问题。

回答（1 个）

Mohith Kulkarni
Mohith Kulkarni 2020-9-25
编辑：Mohith Kulkarni 2020-9-25
By default the optimize parameter is set to 0 for the fitrgp KernelFunction and KernelScale hyperparmeters. Refer to the below code to change the parameter:
params = hyperparameters('fitrgp',X,y);
params(3).Optimize = true; %set KernelFunction optimize to true
params(4).Optimize = true; %set KernelScale optimize to true
In case of "fitrgp" fit function, check Hyperparameter Optimization section of fitrgp arguments for more information. You can check the default Kernel Function and Kernel Parameters of fitrgp fit function here:
KernelFunction and KernelParameters
you can then use the fit function in the objective function.
For more information on performing Bayesian Optimization using bayesopt refer to:
Bayesian Optimization using bayesopt
  4 个评论
显示 2更早的评论
Aep
Aep 2020-10-2
Thank you very much for your answer Mohith. So as you mentioned the inital values are different in each iteration. But considering just one single iteration. We have some initial values. What happens to these values in that specific iteration in bayesopt? Do they change in that iteration? If yes, how?
I apologize if it is a basic question in Gaussian process. I am new to this and I want to make it clear for myself about how Bayesopt does this.
Mahdi Nobar
Mahdi Nobar 2021-12-4
编辑：Mahdi Nobar 2021-12-4
Can someone please answer last comment? @Mohith Kulkarni?

请先登录，再进行评论。

类别

在 Help Center 和 File Exchange 中查找有关 Model Building and Assessment 的更多信息

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by