0.3.2

This release enhances the OBP package in the following ways.

• add some new contents to the obp document: https://zr-obp.readthedocs.io/en/latest/index.html
  • In particular, you can use "off-policy evaluation" section as a textbook about this area
• add obp.dataset.MultiClassToBanditReduction class for handling multi-class classification datasets as bandit feedback #19
  • https://zr-obp.readthedocs.io/en/latest/_autosummary/obp.dataset.multiclass.html#module-obp.dataset.multiclass
  • this will allow researchers to run their synthetic experiments with some multi-class classification datasets easily
  • relevant quickstart and example will be added to the repository soon
• add continuous reward option to obp.dataset.SyntheticBanditDataset
• add squared error (se) option for the evaluation of OPE with obp.ope.OffPolicyEvaluation
• fix some README and docstring inconsistencies
• refactor the dataset and ope modules