History¶
0.10.8 (2022-04-02)¶
Remove dependency Click, since it was not used.
Widen dependency ranges, where appropriate, to make the library easier to install.
0.10.7 (2022-01-30)¶
Expand version range for importlib_metadata to be compatible with other libraries.
0.10.6 (2021-07-15)¶
Fix a crash resulting from bask passing a
numpy.float64
value where anint
was expected.
0.10.5 (2021-03-11)¶
Fix
BayesGPR.sample_y(...)
applying input warping twice. This also fixes incorrect behavior byPVRS
,ThompsonSampling
andVarianceReduction
.
0.10.4 (2021-02-11)¶
Fix a bug in the predictive variance reduction search (PVRS) acquisition function, where the inputs were not warped correctly.
0.10.3 (2021-02-07)¶
Fix a bug where the output
y
was not correctly normalized when passed toBayesGPR.sample(...)
.Fix not adjusting
noise_vector
whennormalize_y=True
.
0.10.2 (2020-09-28)¶
Fix divide by zero encountered in log when evaluating acquisition functions without noise.
0.10.1 (2020-09-26)¶
Bump minimum arviz version to 0.10.0.
0.10.0 (2020-09-20)¶
Add new initialization using the Steinerberger sequence. This works better in high-dimensional problems than the R2 sequence.
Fix exception when a categorical parameter is Iterable.
0.9.3 (2020-09-14)¶
Make default priors for input warping more focused on the identity transform. This fixes issues with overfitting in high noise environments.
0.9.2 (2020-09-04)¶
Fix incorrect recomputation of y mean when using
normalize_y=True
.
0.9.1 (2020-09-02)¶
Fix calculation of max-value entropy search and make it more robust.
0.9.0 (2020-08-31)¶
Add support for automatic input warping. It can be activated by passing
warp_inputs=True
toBayesGPR
.
0.8.0 (2020-08-09)¶
Add
Optimizer.optimum_intervals
which computes the highest density intervals for the optimal parameters.BayesGPR
hasnormalize_y
now set toTrue
by default.Add option to normalize the optimality gap when computing
Optimizer.expected_optimality_gap
orOptimizer.probability_of_optimality
(activated by default).Optimizer.run
now accepts target functions that also return a noise estimate.Optimizer.run
accepts the same arguments asOptimizer.tell
.
0.7.2 (2020-08-01)¶
Fix
guess_priors
not correctly adding the prior for theWhiteKernel
. It is now called directly inBayesGPR.sample
.
0.7.1 (2020-07-28)¶
Restrict length scale bounds of the default kernel to a tighter interval. This should help start the MCMC walkers in a region with higher likelihood.
0.7.0 (2020-07-26)¶
Replace the default inverse gamma distribution prior for the lengthscales by the round-flat distribution.
Fix
guess_priors
to correctly add kernels with multiple lengthscales.
0.6.0 (2020-05-21)¶
Add
Optimizer.expected_optimality_gap
which estimates the expected optimality gap of the current global optimum to random optima sampled from the Gaussian process.Check that the list of priors has the correct length.
Require emcee to be at least version 3.0.
0.5.0 (2020-05-21)¶
Add
Optimizer.probability_of_optimality
which estimates the probability that the current global optimum is optimal within a certain tolerance. This can be used to make stopping rules.
0.4.1 (2020-05-19)¶
Update and fix dependencies.
0.4.0 (2020-04-27)¶
Add
return_policy
parameter toBayesSearchCV
. Allows the user to choose between returning the best observed configuration (in a noise-less setting) or the best predicted configuration (for noisy targets).
0.3.3 (2020-03-16)¶
Fix error occuring when an unknown argument was passed to
Optimizer
.
0.3.0 (2020-03-12)¶
Add predictive variance reduction search criterion. This is the new default acquisition function.
Implement
BayesSearchCV
for use with scikit-learn estimators and pipelines. This is an easy to use drop-in replacement for GridSearchCV or RandomSearchCV. It is implemented as a wrapper around skopt.BayesSearchCV.Determine default kernels and priors to use, if the user provides none.
Add example notebooks on how to use the library.
Add API documentation of the library.
0.2.0 (2020-03-01)¶
Allow user to pass a vector of noise variances to
tell
,fit
andsample
. This can be used to warm start the optimization process.
0.1.2 (2020-02-16)¶
Fix the
tell
method of the optimizer not updating_n_initial_points
correctly, when using replace.
0.1.0 (2020-02-01)¶
First release on PyPI.