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fix: deprecation warning in sklearn.linear_model.LassoLarsIC #2528 #22

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May 12, 2023
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fix: deprecation warning in sklearn.linear_model.LassoLarsIC #2528 #22

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5 changes: 4 additions & 1 deletion shap/explainers/_kernel.py
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Original file line number Diff line number Diff line change
Expand Up @@ -12,6 +12,8 @@
import warnings
import gc
from sklearn.linear_model import LassoLarsIC, Lasso, lars_path
from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import StandardScaler
from tqdm.auto import tqdm
from ._explainer import Explainer

Expand Down Expand Up @@ -562,7 +564,8 @@ def solve(self, fraction_evaluated, dim):
# use an adaptive regularization method
elif self.l1_reg == "auto" or self.l1_reg == "bic" or self.l1_reg == "aic":
c = "aic" if self.l1_reg == "auto" else self.l1_reg
nonzero_inds = np.nonzero(LassoLarsIC(criterion=c).fit(mask_aug, eyAdj_aug).coef_)[0]
model = make_pipeline(StandardScaler(with_mean=False), LassoLarsIC(criterion=c, normalize=False))
nonzero_inds = np.nonzero(model.fit(mask_aug, eyAdj_aug)[1].coef_)[0]

# use a fixed regularization coeffcient
else:
Expand Down