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fix _preprocess_data to align with sklearn refactor #638

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merged 5 commits into from
Jun 22, 2022
Merged

fix _preprocess_data to align with sklearn refactor #638

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804642d
fix _preprocess_data to align with sklearn refactor
fverac Jun 21, 2022
7a54d0a
remove sklearn ceiling
fverac Jun 21, 2022
962e0d7
dummy commit
fverac Jun 21, 2022
2ca55ad
dummy commit 2
fverac Jun 21, 2022
af91018
reintroduce raised sklearn upper limit
fverac Jun 21, 2022
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5 changes: 3 additions & 2 deletions econml/sklearn_extensions/linear_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -22,6 +22,7 @@
from econml.utilities import ndim, shape, reshape, _safe_norm_ppf, check_input_arrays
from sklearn import clone
from sklearn.linear_model import LinearRegression, LassoCV, MultiTaskLassoCV, Lasso, MultiTaskLasso
from sklearn.linear_model._base import _preprocess_data
from sklearn.metrics import r2_score
from sklearn.model_selection import KFold, StratifiedKFold
# TODO: consider working around relying on sklearn implementation details
Expand Down Expand Up @@ -102,7 +103,7 @@ def _fit_weighted_linear_model(self, X, y, sample_weight, check_input=None):
)

# Normalize inputs
X, y, X_offset, y_offset, X_scale = self._preprocess_data(
X, y, X_offset, y_offset, X_scale = _preprocess_data(
X, y, fit_intercept=self.fit_intercept, normalize=False,
copy=self.copy_X, check_input=check_input if check_input is not None else True,
sample_weight=sample_weight)
Expand Down Expand Up @@ -731,7 +732,7 @@ def fit(self, X, y, sample_weight=None, check_input=True):
# Fit weighted lasso with user input
super().fit(X, y, sample_weight, check_input)
# Center X, y
X, y, X_offset, y_offset, X_scale = self._preprocess_data(
X, y, X_offset, y_offset, X_scale = _preprocess_data(
X, y, fit_intercept=self.fit_intercept, normalize=False,
copy=self.copy_X, check_input=check_input, sample_weight=sample_weight)

Expand Down
2 changes: 1 addition & 1 deletion setup.cfg
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Expand Up @@ -33,7 +33,7 @@ packages = find_namespace:
install_requires =
numpy
scipy > 1.4.0
scikit-learn > 0.22.0, < 1.1
scikit-learn > 0.22.0, < 1.2
sparse
joblib >= 0.13.0
statsmodels >= 0.10
Expand Down