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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.