v0.11.0

[0.11.0] - 2022-10-17

Added

• Support for Optuna >3.0
• Example on how to use attrs and dataclass with tpcp
• Added versions for Dataset and CustomOptunaOptimize that work with dataclasses and attrs.
• Added first class support for composite objects (e.g. objects that need a list of other objects as parameters).
  This is basically sklearn pipelines with fewer restrictions (#48).

Changed

• CustomOptunaOptimize now expects a callable to define the study, instead of taking a study object itself.
  This ensures that the study objects can be independent when the class is called as part of cross_validate.
• Parameters are only validated when get_params is called. This reduces the reliance on __init_subclass__ and that
  we correctly wrap the init.
  This makes it possible to easier support attrs and dataclass