How does bayesopt fit a Gaussian process regression model to noisy data?

5 次查看（过去 30 天）
James Finley
James Finley 2019-1-15
评论： Don Mathis 2019-1-17
Hi,
I am using bayesopt to optimise a non-deterministic objective function. I have set the ‘IsObjectiveDeterministic’ input argument to ‘false’, to reflect the stochastic nature of my objective function. My objective function features different levels of noise, depending on the input that is applied to the model.
My question is, does the Gaussian process regression model used in bayesopt assume a constant variance on the noise applied to objective function, or does the GPR model use a non-identically distributed noise for different data points in the observed data? If the latter case is true, how is the noise estimated for different inputs?
Many thanks

请先登录，再回答此问题。

采纳的回答

Don Mathis
Don Mathis 2019-1-16
编辑：Don Mathis 2019-1-16
bayesopt uses fitrgp to fit the GP models, which assumes constant noise everywhere.
https://www.mathworks.com/help/stats/bayesian-optimization-algorithm.html
  2 个评论
James Finley
James Finley 2019-1-17
Hi Don,
Many thanks for your response, you have have answered my question. I was also wondering how fitrgp estimates the variance for the noise in a non-determinisitc system?
Thank you

请先登录，再进行评论。

更多回答（1 个）

Resul Al
Resul Al 2019-1-17
Hi Don,
Is there a way to make fitrgp to estimate heteroscedastic noise, i.e noise variance is not constant everywhere?
Thank you.

类别

在 Help Center 和 File Exchange 中查找有关 Gaussian Process Regression 的更多信息

标签

产品


版本

R2018b

Community Treasure Hunt

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

Start Hunting!

Translated by