v0.4.5#
Changes to
ThresholdOptimizer
:Separate plotting for
ThresholdOptimizer
into its own plotting function.ThresholdOptimizer
now performs validations duringfit
, and not during__init__
. It also stores the fitted given estimator in theestimator_
attribute.ThresholdOptimizer
is now a scikit-learn meta-estimator, and accepts an estimator through theestimator
parameter. To use a pre-fitted estimator, passprefit=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 withsklearn.base.BaseEstimator
andMetaEstimatorMixin
.Remove
ExponentiatedGradientResult
andGridSearchResult
in favor of storing the values and objects resulting from fitting the meta-estimator directly in theExponentiatedGradient
andGridSearch
objects, respectively.Fix regression in input validation that dropped metadata from
X
if it is provided as apandas.DataFrame
.