Release v0.4.5

• Changes to ThresholdOptimizer:
  • Separate plotting for ThresholdOptimizer into its own plotting function.
  • ThresholdOptimizer now performs validations during fit, and not during
    __init__. It also stores the fitted given estimator in the estimator_
    attribute.
  • ThresholdOptmizer is now a scikit-learn meta-estimator, and accepts
    an estimator through the estimator parameter. To use a pre-fitted
    estimator, pass prefit=True.
• Made _create_group_metric_set_() private by prepending with _.
  Also changed the arguments, so that this routine requires
  dictionaries for the predictions and sensitive features. This is a
  breaking change.
• Remove Reduction base class for reductions methods and replace it with
  sklearn.base.BaseEstimator and sklearn.base.MetaEstimatorMixin.
• Remove ExponentiatedGradientResult and GridSearchResult in favor of
  storing the values and objects resulting from fitting the meta-estimator
  directly in the ExponentiatedGradient and GridSearch objects,
  respectively.
• Fix regression in input validation that dropped metadata from X if it is
  provided as a pandas.DataFrame.