How to use Bayesian Optimization?
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I'm trying to run the following Mathworks example with my own X and Y:
"Tune Random Forest Using Quantile Error and Bayesian Optimization"
But, I'm getting the following error:
Undefined function or variable 'Y'.
I have attached the modified code (place both files in one folder on your PC drive). Can anyone help?
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Answers (1)
Don Mathis
on 20 Apr 2017
You need to pass Y into oobErrRF. Change its first line to
function oobErr = oobErrRF(params,X,Y)
And change the call on line 66 of your main file to
results = bayesopt(@(params)oobErrRF_editted(params,X,Y),hyperparametersRF,...
That fixes your error. But after that you get a new error, because inside oobErrRF you're calling oobQuantileError on a classification random forest, while it's only defined for regression random forests. Are you trying to do classification or regression?
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Don Mathis
on 27 Apr 2017
Yes you can. I edited your code to call 'oobError' instead of 'oobQuantileError', and took the mean over all trees. I also told your final 'Mdl' to train with Method 'classification' and turned on 'OOBPredictions' so you can see the performance of the final model. I also told 'bayesopt' to use Verbose=1. I've attached the edited files.
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