v0.7rc2

Merge pull request #816 from holgern/fix_pypi_deploy

[MRG] Fix pypi deploy

v0.7rc1

Update README.rst

I will help in maintaining scikit-optimize

Highly composite six - v0.6

Version 0.6

Highly composite six.

New features

• plot_regret function for plotting the cumulative regret;
  The purpose of such plot is to access how much an optimizer
  is effective at picking good points.
• CheckpointSaver that can be used to save a
  checkpoint after each iteration with skopt.dump
• Space.from_yaml()
  to allow for external file to define Space parameters

Bug fixes

• Fixed numpy broadcasting issues in gaussian_ei, gaussian_pi
• Fixed build with newest scikit-learn
• Use native python types inside BayesSearchCV
• Include fit_params in BayesSearchCV refit

Maintenance

• Added versioneer support, to reduce changes with new version of the skopt

v0.6rc1

Release candidate for v0.6.

v0.5.2

Version 0.5.2

Bug fixes

• Separated n_points from n_jobs in BayesSearchCV.
• Dimensions now support boolean np.arrays.

Maintenance

• matplotlib is now an optional requirement (install with pip install 'scikit-optimize[plots]')

v0.5.1 - re-release

This release super-seeds v0.5. We made a mistake tagging the v0.5rc1 on PyPI and releasing this to replace v0.5.

High five - v0.5

Version 0.5

High five!

New features

• Single element dimension definition, which can be used to fix the
  value of a dimension during optimization.
• total_iterations property of BayesSearchCV that counts total
  iterations needed to explore all subspaces.
• Add iteration event handler for BayesSearchCV, useful for early
  stopping inside BayesSearchCV search loop.
• Added utils.use_named_args decorator to help with unpacking
  named dimensions when calling an objective function.

Bug fixes

• Removed redundant estimator fitting inside BayesSearchCV.
• Fixed the log10 transform for Real dimensions that would lead
  to values being out of bounds.

v0.5rc1

Release candidate for v0.5.

Go forth - v0.4

Version 0.4

Go forth!

New features

• Support early stopping of optimization loop.
• Benchmarking scripts to evaluate performance of different surrogate models.
• Support for parallel evaluations of the objective function via several
  constant liar stategies.
• BayesSearchCV as a drop in replacement for scikit-learn's GridSearchCV.
• New acquisition functions "EIps" and "PIps" that takes into account
  function compute time.

Bug fixes

• Fixed inference of dimensions of type Real.

API changes

• Change interface of GradientBoostingQuantileRegressor's predict method to
  match return type of other regressors
• Dimensions of type Real are now inclusive of upper bound.

v0.4rc1

Release candidate for v0.4