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API Deprecate n_features_in_ from Dummy* #20960

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Merged
merged 2 commits into from
Sep 7, 2021
Merged

API Deprecate n_features_in_ from Dummy* #20960

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a3f7d14
ENH Adds feature_names_in_ for estimators that do not validate
thomasjpfan Sep 7, 2021
ffc5018
DOC Adds whats new
thomasjpfan Sep 7, 2021
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7 changes: 7 additions & 0 deletions doc/whats_new/v1.0.rst
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Expand Up @@ -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`
.......................

Expand Down
36 changes: 29 additions & 7 deletions sklearn/dummy.py
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Expand Up @@ -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
Expand Down Expand Up @@ -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.
Expand Down Expand Up @@ -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:
Expand Down Expand Up @@ -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.
Expand Down Expand Up @@ -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.
Expand Down Expand Up @@ -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.")

Expand Down Expand Up @@ -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
5 changes: 4 additions & 1 deletion sklearn/tests/test_dummy.py
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Expand Up @@ -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