fitrgp hyperparameter optimization for noisy functions
2 次查看(过去 30 天)
显示 更早的评论
hyperparameter optimization for fitrgp hyperparameters in matlab there is {'BasisFunction','KernelFunction','KernelScale','Sigma','Standardize'} that can be optimized. However, in noisy cases we have a sigma parameter (different than kernel sigma) added to the diagonal of the kernel based on Rasmussen, 2006. How can I specify or optimize that sigma besides sigmaf and sigmal which are the kernel hyperparameters?
0 个评论
回答(2 个)
Aditya Patil
2020-9-21
From my understanding, you want to set the noise variance() parameter mentioned in the book. You can do so using 'Sigma' name value pair. Note that 'Sigma' sets the standard deviation. You can find more about it in the documentation here
0 个评论
Hyunjung Lee
2020-12-4
The nugget or jitter can be "addressed" by adding a small number to the main diagonal of the correlation matrix.
I agree with Aditya Patil. In fitrgp, that can be done via 'Sigma'. For example,
tau=1e-3; %some small value
gpmodel=fitrgp(X,y,'FitMethod','none','Sigma',tau);
By setting 'FitMethod' to 'none', the nugget term remains as the value you assign.
0 个评论
另请参阅
产品
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!