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[WIP] FIX make ThresholdOptimizer sklearn compatible #342

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[WIP] FIX make ThresholdOptimizer sklearn compatible #342

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3 changes: 1 addition & 2 deletions fairlearn/postprocessing/_threshold_optimizer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -64,12 +64,11 @@ class ThresholdOptimizer(BaseEstimator, ClassifierMixin, MetaEstimatorMixin):
:type: bool, default=False
"""

def __init__(self, *, estimator=None,
def __init__(self, estimator=None, *,
constraints=DEMOGRAPHIC_PARITY, grid_size=1000, flip=True,
prefit=False):
self.grid_size = grid_size
self.flip = flip
self.post_processed_predictor_by_sensitive_feature = None
self.constraints = constraints
self.estimator = estimator
self.prefit = prefit
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7 changes: 7 additions & 0 deletions test/unit/postprocessing/test_threshold_optimization.py
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Expand Up @@ -4,6 +4,8 @@
from copy import deepcopy
import numpy as np
import pytest
from sklearn.utils.estimator_checks import parametrize_with_checks

from fairlearn.postprocessing._constants import DEMOGRAPHIC_PARITY, EQUALIZED_ODDS
from fairlearn._input_validation import \
(_MESSAGE_Y_NONE,
Expand Down Expand Up @@ -443,3 +445,8 @@ def create_adjusted_predictor(threshold_optimization_method, sensitive_features,

return lambda sensitive_features_, scores: _vectorized_prediction(
post_processed_predictor_by_sensitive_feature, sensitive_features_, scores)


@parametrize_with_checks([ThresholdOptimizer])
def test_sklearn_compatibility(estimator, check):
check(estimator)