introduce sample weights

ccomkhj · Nov 27, 2023 · 2973a73 · 2973a73
1 parent 185e463
commit 2973a73
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Showing 2 changed files with 4 additions and 4 deletions.
diff --git a/constrainedML/multi_selective_drop_positive_linear_regression.py b/constrainedML/multi_selective_drop_positive_linear_regression.py
@@ -35,8 +35,8 @@ def __init__(
         self.max_coef_ = min_coef_
         self.min_coef_ = max_coef_
 
-    def fit(self, X, y, min_coef=None, max_coef=None):
-        X, y, X_offset, y_offset, X_scale = self._preprocess(X, y)
+    def fit(self, X, y, min_coef=None, max_coef=None, sample_weight=None):
+        X, y, X_offset, y_offset, X_scale = self._preprocess(X, y, sample_weight)
 
         original_feature_count = X.shape[-1]
         self.min_coef_ = self._verify_coef(

diff --git a/constrainedML/selective_drop_positive_linear_regression.py b/constrainedML/selective_drop_positive_linear_regression.py
@@ -9,8 +9,8 @@
 class SelectiveDropPositiveLinearRegression(BaseSelectiveDropPositiveLinearRegression):
     """ """
 
-    def fit(self, X, y, min_coef=None, max_coef=None):
-        X, y, X_offset, y_offset, X_scale = self._preprocess(X, y)
+    def fit(self, X, y, min_coef=None, max_coef=None, sample_weight=None):
+        X, y, X_offset, y_offset, X_scale = self._preprocess(X, y, sample_weight)
         feature_count = X.shape[-1]
         self.min_coef_ = self._verify_coef(feature_count, min_coef, -np.inf).flatten()
         self.max_coef_ = self._verify_coef(feature_count, max_coef, np.inf).flatten()