FIX DummyRegressor overriding constant (scikit-learn#22486)

doc/whats_new/v1.1.rst

@@ -245,6 +245,12 @@ Changelog
  :class:`discriminant_analysis.LinearDiscriminantAnalysis`. :pr:`22120` by
  `Thomas Fan`_.
 
+:mod:`sklearn.dummy`
+....................
+
+- |Fix| :class:`dummy.DummyRegressor` no longer overrides the `constant`
+ parameter during `fit`. :pr:`22486` by `Thomas Fan`_.
+
 :mod:`sklearn.ensemble`
 .......................
 

sklearn/dummy.py

@@ -606,20 +606,18 @@ def fit(self, X, y, sample_weight=None):
  "when the constant strategy is used."
  )
 
- self.constant = check_array(
+ self.constant_ = check_array(
  self.constant,
  accept_sparse=["csr", "csc", "coo"],
  ensure_2d=False,
  ensure_min_samples=0,
  )
 
- if self.n_outputs_ != 1 and self.constant.shape[0] != y.shape[1]:
+ if self.n_outputs_ != 1 and self.constant_.shape[0] != y.shape[1]:
  raise ValueError(
  "Constant target value should have shape (%d, 1)." % y.shape[1]
  )
 
- self.constant_ = self.constant
-
  self.constant_ = np.reshape(self.constant_, (1, -1))
  return self
 

sklearn/tests/test_dummy.py

@@ -425,6 +425,9 @@ def test_constant_strategy_regressor():
  reg.fit(X, y)
  assert_array_equal(reg.predict(X), [43] * len(X))
 
+ # non-regression test for #22478
+ assert not isinstance(reg.constant, np.ndarray)
+
 
 def test_constant_strategy_multioutput_regressor():