Effacer les filtres
Effacer les filtres

How to extract hyper parameters during Bayesian optimization

6 vues (au cours des 30 derniers jours)
Fab le 1 Mar 2019
Commenté : Andrea Testa le 24 Mar 2022
Hi all,
I am new to using the bayesopt Matlab function and I was trying to test it on a toy problem.
I realize that bayesopt uses the "ardmatern52" Kernel function, which allows different length scales for multiple hyperparameters, and I wanted to have access to estimates of hyper parameters produced by the Bayesian Optimization function. In my understanding, these estimates are produced after evals by the fitrgp function; however, it seems that they somehow get lost and become unaccessible when a call to bayesopt is made. Any idea on how to access these estimates at the end of a Bayesian Optimization?
Currently working with R2016b

Réponse acceptée

Don Mathis
Don Mathis le 1 Mar 2019
There are many hidden properties in the BayesianOptimization object that is returned by bayesopt. One of them is ObjectiveFcnGP, which is the last Gaussian Process model that was fit to the observed function evaluation data. Here's an example of how to get the kernel parameters from that model (using R2018b):
Run bayesopt:
load ionosphere
rng default
num = optimizableVariable('n',[1,30],'Type','integer');
dst = optimizableVariable('dst',{'chebychev','euclidean','minkowski'},'Type','categorical');
c = cvpartition(351,'Kfold',5);
fun = @(x)kfoldLoss(fitcknn(X,Y,'CVPartition',c,'NumNeighbors',x.n,...
results = bayesopt(fun,[num,dst],'Verbose',0,...
Get the final GP model:
gp = results.ObjectiveFcnGP
Get the kernel parameters from that:
gp.KernelInformation % look at kernel information
kparams = gp.KernelInformation.KernelParameters
You can see all the properties (hidden, private or otherwise) by doing this:
s = struct(results)
Then you can access what you want.
  5 commentaires
Don Mathis
Don Mathis le 23 Mar 2022
Try results.ObjectiveFcnModel.Model
Andrea Testa
Andrea Testa le 24 Mar 2022

Connectez-vous pour commenter.

Plus de réponses (0)




Community Treasure Hunt

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

Start Hunting!

Translated by