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@andy-esch
Numpy 1.12.1
Pandas 0.19.2
SciPy 0.19.0
sklearn 0.18.1
pysal 1.13.0
cvxopt 1.1.9 (http://cvxopt.org/install/index.html)
keras 2.0.2
tensorflow (http://tflearn.org/installation…
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Hi,
i try to run
```
OPT_Res
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Basically what title says. When using GPyOpt to optimize an externally evaluated function, the maximize flag has no effect.
I would expect this snippet to maximize based on the inputs:
Snippet 1:
…
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Whilst training a model using a BayesianOptimization tuner on a Ubuntu 22.04 system, as the programs runs, the program continues to increase its usage of RAM without releasing it in-between trials, un…
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I can't use constraints.
Environment:
Python 3.6.4
GPyOpt 1.2.1
```python
import GPyOpt
def objective(x):
return (x[:,0]-0.1)**2
domain = [{'name': 'var_1', 'type': 'continuous', 'doma…
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Hi Team,
I dont have a optimization function, I pass it as None -
GPyOpt.methods.BayesianOptimization(None, domain=bounds,
model_type= 'GP_MCMC',…
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I would like to use non-numerical categorical variables in GPyOpt.
From the error, I understand such variables are being treated in the same way as `DiscreteVariables`, but it is not possible to conv…
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Currently optimization process is a fully-automatic blackbox. I mean, you call fmin.bayes_optimization with appropriate arguments, wait for some time and get the answers together with various running …
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When defining toy example like this:
```
import GPyOpt
def f(x):
print(x)
return (2*x)**2
bounds = [{'name': 'var_1', 'type': 'continuous', 'domain': (-1, 1)}]
task = GPyOpt.metho…