rBayesianOptimization
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yanyachen
Bayesian Optimization of Hyperparameters
Hello, I am having this problem. When I run the function, it shows *Error in if (!(lo
Wondering if anyone else has observed this. I have 128GB RAM computer and trying to optimize ~6 parameters. Initially the function call triggers the child function and next set of...
Error in chol.default(x = Sig) : the leading minor of order 52 is not positive definite Calls: BayesianOptimization ... fn -> GP_deviance -> sig_invb -> chol -> chol.default In addition:...
The rBayesianOptimization sometimes generates an error `Non-finite value supplied by optim` during the iteration. The numbers of round in which I get this error are different every time. Below is...
I am trying to optmize a xgboost algorithm, the 'ntree' is among the parameter set I want to optmize and in the end the BayesianOptimization function returns the "best set"...
I'm using rBayesianOptimization to find the best combination of hyperparameters to use in a XGBoost model. From a grid of these hyperparameters, i define a function (object "FUN") that runs...
Hi, I really enjoy your code and try to implement it on the gaussian process regression based on kernlab package. Here is my code `x
Just an FYI in case anyone gets a GP_deviance error. Thought I should share this, in the obscure chance it will help someone else. Took me a good 2 hours...
Currently, the bayesian optimization uses gaussian process as the surrogate model. The research shows that random forest underlying process ahcieves fastest convergence: http://ceur-ws.org/Vol-1201/paper-06.pdf
after running code from https://cran.r-project.org/web/packages/rBayesianOptimization/rBayesianOptimization.pdf Example 2: Parameter Tuning There is mistake: Error in (function (max.depth, min_child_weight, subsample) : object 'test.auc.mean' not found In addition: Warning message: In .Internal(gc(verbose, reset))...
