v0.4.6#
Handle case where reductions relabeling results in a single class
Refactor metrics:
Remove
GroupMetricResult
type in favor of a Bunch.Rename and slightly update signatures: *
metric_by_group
changed togroup_summary
*make_group_metric
changed tomake_metric_group_summary
Add group summary transformers
{difference,ratio,group_min,group_max}_from_group_summary
.Add factory
make_derived_metric
.
Add new metrics:
base metrics
{true,false}_{positive,negative}_rate
group summary metrics
<metric>_group_summary
derived metrics
<metric>_{difference,ratio,group_min,group_max}
disparity metrics
{demographic_parity,equalized_odds}_{difference,ratio}
Remove metrics:
fallout_rate
in favor offalse_positive_rate
miss_rate
in favor offalse_negative_rate
specificity_score
in favor oftrue_negative_rate
Change from public to private:
mean_{over,under}prediction
and{balanced_,}root_mean_squared_error
changed to the versions with a leading underscore
Fix warning due to changing default
dtype
when creating an emptypandas.Series
.Enable
fairlearn.reductions.GridSearch
for more than two sensitive features values.Add new disparity constraints for reductions methods as moments in
fairlearn.reductions
including:TruePositiveRateDifference
ratio options for all existing constraints in addition to the default, i.e., difference between groups w.r.t. the relevant metric.
Make
ExponentiatedGradient
require 0-1 labels for classification problems, pending a better solution for Issue 339.