Scikit Optimize Versions Save

What's Changed

• [MRG]Add hollow iterations early stopper by @ludaavics in https://github.com/scikit-optimize/scikit-optimize/pull/917
• Doc line, logspace call, set_transformer default parameter misstype, … by @GCidd in https://github.com/scikit-optimize/scikit-optimize/pull/921
• Revert change to plot_histogramm by @holgern in https://github.com/scikit-optimize/scikit-optimize/pull/942
• [MRG] Fixes GaussianProcessRegressor for sklearn >= 0.23 by @holgern in https://github.com/scikit-optimize/scikit-optimize/pull/943
• [MRG] Refactor Sobol' API by @tupui in https://github.com/scikit-optimize/scikit-optimize/pull/955
• docs: fix simple typo, stategies -> strategies by @timgates42 in https://github.com/scikit-optimize/scikit-optimize/pull/979
• [MRG] Correct documented default is_int for Normalize. by @gcp in https://github.com/scikit-optimize/scikit-optimize/pull/1019
• [MRG] add ThresholdStopper() by @GuillaumeSimo in https://github.com/scikit-optimize/scikit-optimize/pull/1000
• [MRG] Check whether prior values are valid. by @gcp in https://github.com/scikit-optimize/scikit-optimize/pull/1020
• Fix numpy Deprecation errors by @xmatthias in https://github.com/scikit-optimize/scikit-optimize/pull/1023
• Remove BayesSearchCV(iid=) parameter deprecated in sklearn 0.24 by @kernc in https://github.com/scikit-optimize/scikit-optimize/pull/988
• Re-add BayesSearchCV.best_score_ needed by some examples by @kernc in https://github.com/scikit-optimize/scikit-optimize/pull/1031
• Revert "Re-add BayesSearchCV.best_score_ needed by some examples" by @kernc in https://github.com/scikit-optimize/scikit-optimize/pull/1032
• Use deepcopy to prevent reference cycles in Optimizer by @freddyaboulton in https://github.com/scikit-optimize/scikit-optimize/pull/1029
• [MRG] Fixed grammatical error in docs: 'less' vs 'fewer' by @samuelstevens in https://github.com/scikit-optimize/scikit-optimize/pull/1040
• [MRG] update packges in circleci deps by @QuentinSoubeyran in https://github.com/scikit-optimize/scikit-optimize/pull/1069
• [MRG] Fix GaussianProcessRegressor for scikit-learn 1.0 by @QuentinSoubeyran in https://github.com/scikit-optimize/scikit-optimize/pull/1063
• Fix remaining sklearn 1.0 return_X_y= error by @kernc in https://github.com/scikit-optimize/scikit-optimize/pull/1078
• MNT: Fix CircleCI builds by unpinning + full docs for PRs by @kernc in https://github.com/scikit-optimize/scikit-optimize/pull/1079
• MNT: Fix "LaTeX Error: File 'tgtermes.sty' not found." on CircleCI by @kernc in https://github.com/scikit-optimize/scikit-optimize/pull/1080

New Contributors

• @ludaavics made their first contribution in https://github.com/scikit-optimize/scikit-optimize/pull/917
• @GCidd made their first contribution in https://github.com/scikit-optimize/scikit-optimize/pull/921
• @tupui made their first contribution in https://github.com/scikit-optimize/scikit-optimize/pull/955
• @timgates42 made their first contribution in https://github.com/scikit-optimize/scikit-optimize/pull/979
• @GuillaumeSimo made their first contribution in https://github.com/scikit-optimize/scikit-optimize/pull/1000
• @xmatthias made their first contribution in https://github.com/scikit-optimize/scikit-optimize/pull/1023
• @kernc made their first contribution in https://github.com/scikit-optimize/scikit-optimize/pull/988
• @freddyaboulton made their first contribution in https://github.com/scikit-optimize/scikit-optimize/pull/1029
• @samuelstevens made their first contribution in https://github.com/scikit-optimize/scikit-optimize/pull/1040
• @QuentinSoubeyran made their first contribution in https://github.com/scikit-optimize/scikit-optimize/pull/1069

Full Changelog: https://github.com/scikit-optimize/scikit-optimize/compare/v0.8.1...v0.9.0

• GaussianProcessRegressor from sklearn >= 0.23 normalizes the variance to 1, which needs to be taken into account. This release handles this and returns the same results as on sklearn <= 0.23

• n_jobs support was added to Optimizer and fixed for forest_minimize #884

• Allow dimension selection for plot_objective and plot_evaluations and add plot_histogram and plot_objective_2D. Plot code has been refactored. #848

• Initial sampling generation from latin hypercube, sobol, hammersly and halton is possible and can be set in all optimizers #835

• Improve sampler and add grid sampler #851

• Fix library for scikit-learn >= 0.23. numpy MaskArray is replaced by numpy.ma.array. y_normalize=False has been added and initial runs has been increased. #939

• Integer transform and inverse_transform for normalize #880

• Add is_constant property to dimension and n_constant_dimensions property to Space #883

• Skip constant dimensions for plot_objective and plot_evaluations to allow plots using BayesSearchCV #888

• Fix Fix Optimizer for full categorical spaces #874

• Improve circle ci #852

• Add project toml and adapt minimal numpy, scipy, pyyaml and joblib version in setup.py #850

Fix wrong entry in MANIFEST.in for allowing the conda package to be build.

Add missing license to source package (Fix conda build).

Version 0.7.2

New features

• Add expected_minimum_random_sampling
• New plot examples
• Add more parameter to plot_objective
• Return ordereddict in point_asdict
• update_next() and get_results() added to Optimize

Bug fixes

• Fix searchcv rank (issue #831)
• Fix random forest regressor (issue #766)
• Fix doc examples
• Fix integer normalize by using round()
• Fix random forest regressor (Add missing min_impurity_decrease)

Maintenance

• Fix license detection in github
• Add doctest to CI

Version 0.7.1

New features

• Sphinx documentation
• notebooks are replaced by sphinx-gallery
• New StringEncoder, can be used in Categoricals
• Remove string conversion in Identity
• dtype can be set in Integer and Real

Bug fixes

• Fix categorical space (issue #821)
• int can be set as dtype to fix issue #790

Maintenance

• Old pdoc scripts are removed and replaced by sphinx

Version 0.7

New features

• Models queue has now a customizable size (model_queue_size).
• Add log-uniform prior to Integer space
• Support for plotting categorical dimensions

Bug fixes

• Allow BayesSearchCV to work with sklearn 0.21
• Reduce the amount of deprecation warnings in unit tests

Maintenance

• joblib instead of sklearn.externals.joblib
• Improve travis CI unit tests (Different sklearn version are checked)
• Added versioneer support, to keep things simple and to fix pypi deploy