v0.10.0

This release includes almost all open PR from the original repository since 2020. The original scikit-optimize repo is now archived, I will continue development on https://github.com/holgern/scikit-optimize. Please add issues and PRs here.

• Feature Add support for multimetric scoring to :obj:skopt.searchcv.BayesSearchCV.
• Feature Evaluate random point instead of using point twice in :obj:skopt.optimizer.Optimizer.
• Feature :obj:skopt.callback.CheckpointSaver can now recycle previous function evaluations
• Feature finish CI move to GHA
• Fix Keep order of variables in LabelEncoder
• Feature add from_df method to Space class
• Fix Fix :obj:skopt.plots.plot_evaluations incorrectly handling dimensions
  as categorical dimensions when constant dimension are ignored due to wrong
  indexing.
• Fix Improved Bayesian Optimization documentation
• Fix Replace occurrences of mse with squared_error
• Fix numpy.int issue
• Feature add standard deviation Stopper for Gaussian process
• Feature Implement MES and PVRS acquisition functions.
• Fix Fix tuple index out of range on plot
• Fix Fixes Grid sampling with border="only"
• Fix Update plot_evaluations param
• Fix Fix plot_gaussian_process not working with ps-acquisition
• Feature Make Real and Integer raise error when prior is log-uniform and bounds contain zero
• Fix Better use proper parsing of the scikit-learn version numbers.
• Feature Test DeltaYStopper with minimize functions fixes
• Fix dimension mismatch with gp_minimize in Matern kernel when nu=0.5
• Fix GPR with noise fix
• Feature Add constrained optimization
• Feature Add 'ax' argument to all plotting functions
• API Improve and tighten the inference of skopt.space.space.Dimension
  objects from tuple, dict and numpy array. See the documentation of
  skopt.space.space.check_dimension for details. The old behavior is
  retained for a transitionary period; a warning is raised if the inference
  would change under the new scheme.
• Minor documentation improvements.
• Various small bugs and fixes.