gaussian_lcb(X, model, kappa=1.96, return_grad=False)¶
Use the lower confidence bound to estimate the acquisition values.
The trade-off between exploitation and exploration is left to be controlled by the user through the parameter
- Xarray-like, shape (n_samples, n_features)
Values where the acquisition function should be computed.
- modelsklearn estimator that implements predict with
The fit estimator that approximates the function through the method
predict. It should have a
return_stdparameter that returns the standard deviation.
- kappafloat, default 1.96 or ‘inf’
Controls how much of the variance in the predicted values should be taken into account. If set to be very high, then we are favouring exploration over exploitation and vice versa. If set to ‘inf’, the acquisition function will only use the variance which is useful in a pure exploration setting. Useless if
methodis not set to “LCB”.
- return_gradboolean, optional
Whether or not to return the grad. Implemented only for the case where
Xis a single sample.
- valuesarray-like, shape (X.shape,)
Acquisition function values computed at X.
- gradarray-like, shape (n_samples, n_features)
Gradient at X.