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FIX: resolve sklearn 1.9 compatibility for WeightedLassoCV n_alphas deprecation (#1032 ) #1046

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FIX: resolve sklearn 1.9 compatibility for WeightedLassoCV n_alphas deprecation (#1032 ) #1046

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32 changes: 28 additions & 4 deletions econml/sklearn_extensions/linear_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -430,14 +430,17 @@ def __init__(self, eps=1e-3, n_alphas=100, alphas=None, fit_intercept=True,
import sklearn

if parse(sklearn.__version__) >= parse("1.7"):
# In sklearn 1.7+, 'alphas' accepts an int (number of alphas) or
# array-like (explicit alpha values). 'n_alphas' is deprecated in
# 1.7 and removed in 1.9.
alphas_param = alphas if alphas is not None else n_alphas
super().__init__(
eps=eps, alphas=alphas if alphas is not None else n_alphas,
eps=eps, alphas=alphas_param,
fit_intercept=fit_intercept,
precompute=precompute, max_iter=max_iter, tol=tol, copy_X=copy_X,
cv=cv, verbose=verbose, n_jobs=n_jobs, positive=positive,
random_state=random_state, selection=selection)
self.n_alphas = n_alphas
self.alphas = alphas
else:
super().__init__(
eps=eps, n_alphas=n_alphas, alphas=alphas,
Expand All @@ -446,6 +449,15 @@ def __init__(self, eps=1e-3, n_alphas=100, alphas=None, fit_intercept=True,
cv=cv, verbose=verbose, n_jobs=n_jobs, positive=positive,
random_state=random_state, selection=selection)

def get_params(self, deep=True):
"""Get parameters, excluding deprecated n_alphas on sklearn >= 1.7."""
params = super().get_params(deep=deep)
from packaging.version import parse
import sklearn
if parse(sklearn.__version__) >= parse("1.7"):
params.pop('n_alphas', None)
return params

def fit(self, X, y, sample_weight=None):
"""Fit model with coordinate descent.

Expand Down Expand Up @@ -554,14 +566,17 @@ def __init__(self, eps=1e-3, n_alphas=100, alphas=None, fit_intercept=True,
import sklearn

if parse(sklearn.__version__) >= parse("1.7"):
# In sklearn 1.7+, 'alphas' accepts an int (number of alphas) or
# array-like (explicit alpha values). 'n_alphas' is deprecated in
# 1.7 and removed in 1.9.
alphas_param = alphas if alphas is not None else n_alphas
super().__init__(
eps=eps, alphas=alphas if alphas is not None else n_alphas,
eps=eps, alphas=alphas_param,
fit_intercept=fit_intercept,
max_iter=max_iter, tol=tol, copy_X=copy_X,
cv=cv, verbose=verbose, n_jobs=n_jobs,
random_state=random_state, selection=selection)
self.n_alphas = n_alphas
self.alphas = alphas
else:
super().__init__(
eps=eps, n_alphas=n_alphas, alphas=alphas,
Expand All @@ -570,6 +585,15 @@ def __init__(self, eps=1e-3, n_alphas=100, alphas=None, fit_intercept=True,
cv=cv, verbose=verbose, n_jobs=n_jobs,
random_state=random_state, selection=selection)

def get_params(self, deep=True):
"""Get parameters, excluding deprecated n_alphas on sklearn >= 1.7."""
params = super().get_params(deep=deep)
from packaging.version import parse
import sklearn
if parse(sklearn.__version__) >= parse("1.7"):
params.pop('n_alphas', None)
return params

def fit(self, X, y, sample_weight=None):
"""Fit model with coordinate descent.

Expand Down