API Deprecate n_features_in_ from Dummy* (#20960)

thomasjpfan · web-flow · commit 5bf94911a8f9 · 2021-09-07T09:34:08.000+01:00
diff --git a/doc/whats_new/v1.0.rst b/doc/whats_new/v1.0.rst
@@ -335,6 +335,13 @@ Changelog
   in 1.2. Use the new parameters `alpha_W` and `alpha_H` instead. :pr:`20512` by
   :user:`Jérémie du Boisberranger <jeremiedbb>`.
 
+:mod:`sklearn.dummy`
+....................
+
+- |API| Attribute `n_features_in_` in :class:`dummy.DummyRegressor` and
+  :class:`dummy.DummyRegressor` is deprecated and will be removed in 1.2.
+  :pr:`20960` by `Thomas Fan`_.
+
 :mod:`sklearn.ensemble`
 .......................
 
diff --git a/sklearn/dummy.py b/sklearn/dummy.py
@@ -10,6 +10,7 @@
 from .base import BaseEstimator, ClassifierMixin, RegressorMixin
 from .base import MultiOutputMixin
 from .utils import check_random_state
+from .utils import deprecated
 from .utils.validation import _num_samples
 from .utils.validation import check_array
 from .utils.validation import check_consistent_length
@@ -75,10 +76,12 @@ class DummyClassifier(MultiOutputMixin, ClassifierMixin, BaseEstimator):
     n_outputs_ : int
         Number of outputs.
 
-    n_features_in_ : int
-        Number of features seen during :term:`fit`.
+    n_features_in_ : `None`
+        Always set to `None`.
 
         .. versionadded:: 0.24
+        .. deprecated:: 1.0
+            Will be removed in 1.0
 
     sparse_output_ : bool
         True if the array returned from predict is to be in sparse CSC format.
@@ -164,8 +167,6 @@ def fit(self, X, y, sample_weight=None):
 
         self.n_outputs_ = y.shape[1]
 
-        self.n_features_in_ = None  # No input validation is done for X
-
         check_consistent_length(X, y)
 
         if sample_weight is not None:
@@ -421,6 +422,16 @@ def score(self, X, y, sample_weight=None):
             X = np.zeros(shape=(len(y), 1))
         return super().score(X, y, sample_weight)
 
+    # TODO: Remove in 1.2
+    # mypy error: Decorated property not supported
+    @deprecated(  # type: ignore
+        "`n_features_in_` is deprecated in 1.0 and will be removed in 1.2."
+    )
+    @property
+    def n_features_in_(self):
+        check_is_fitted(self)
+        return None
+
 
 class DummyRegressor(MultiOutputMixin, RegressorMixin, BaseEstimator):
     """Regressor that makes predictions using simple rules.
@@ -459,10 +470,12 @@ class DummyRegressor(MultiOutputMixin, RegressorMixin, BaseEstimator):
         Mean or median or quantile of the training targets or constant value
         given by the user.
 
-    n_features_in_ : int
-        Number of features seen during :term:`fit`.
+    n_features_in_ : `None`
+        Always set to `None`.
 
         .. versionadded:: 0.24
+        .. deprecated:: 1.0
+            Will be removed in 1.0
 
     n_outputs_ : int
         Number of outputs.
@@ -518,7 +531,6 @@ def fit(self, X, y, sample_weight=None):
             )
 
         y = check_array(y, ensure_2d=False)
-        self.n_features_in_ = None  # No input validation is done for X
         if len(y) == 0:
             raise ValueError("y must not be empty.")
 
@@ -656,3 +668,13 @@ def score(self, X, y, sample_weight=None):
         if X is None:
             X = np.zeros(shape=(len(y), 1))
         return super().score(X, y, sample_weight)
+
+    # TODO: Remove in 1.2
+    # mypy error: Decorated property not supported
+    @deprecated(  # type: ignore
+        "`n_features_in_` is deprecated in 1.0 and will be removed in 1.2."
+    )
+    @property
+    def n_features_in_(self):
+        check_is_fitted(self)
+        return None
diff --git a/sklearn/tests/test_dummy.py b/sklearn/tests/test_dummy.py
@@ -733,4 +733,7 @@ def test_n_features_in_(Dummy):
     d = Dummy()
     assert not hasattr(d, "n_features_in_")
     d.fit(X, y)
-    assert d.n_features_in_ is None
+
+    with pytest.warns(FutureWarning, match="`n_features_in_` is deprecated"):
+        n_features_in = d.n_features_in_
+    assert n_features_in is None
