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FIX Adds check_array to inverse_transform of StandardScaler #19356

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Merged
merged 11 commits into from
Mar 23, 2021
Merged

FIX Adds check_array to inverse_transform of StandardScaler #19356

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b7ecc50
add check_array to inverse_transform of StandardScaler
makoeppel Feb 5, 2021
728983d
add suggestions of using self.copy
makoeppel Feb 5, 2021
3ab5013
add non-regression test
makoeppel Feb 5, 2021
704ab29
Merge branch 'main' of https://github.com/scikit-learn/scikit-learn i…
makoeppel Feb 8, 2021
28f7290
ensure_2d=False
makoeppel Feb 11, 2021
eaff378
Merge main into check_array_StandardScaler
makoeppel Feb 15, 2021
fd20fa0
rm csr check and array conversions
makoeppel Feb 15, 2021
eaa6a8c
Merge upstream/main into check_array_StandardScaler
makoeppel Feb 22, 2021
17dd5be
add suggestions for test_standard_check_array_of_inverse_transform
makoeppel Feb 22, 2021
83eb055
Merge remote-tracking branch 'origin/main' into pr/19356
thomasjpfan Mar 23, 2021
f1fde58
DOC Adds whats new
thomasjpfan Mar 23, 2021
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3 changes: 3 additions & 0 deletions doc/whats_new/v1.0.rst
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Expand Up @@ -187,6 +187,9 @@ Changelog
positioning strategy ``knots``.
:pr:`18368` by :user:`Christian Lorentzen <lorentzenchr>`.

- |Fix| :meth:`preprocessing.StandardScaler.inverse_transform` now
correctly handles integer dtypes. :pr:`19356` by :user:`makoeppel`.

:mod:`sklearn.tree`
...................

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11 changes: 3 additions & 8 deletions sklearn/preprocessing/_data.py
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Expand Up @@ -911,22 +911,17 @@ def inverse_transform(self, X, copy=None):
check_is_fitted(self)

copy = copy if copy is not None else self.copy
X = check_array(X, accept_sparse='csr', copy=copy, ensure_2d=False,
dtype=FLOAT_DTYPES, force_all_finite="allow-nan")

if sparse.issparse(X):
if self.with_mean:
raise ValueError(
"Cannot uncenter sparse matrices: pass `with_mean=False` "
"instead See docstring for motivation and alternatives.")
if not sparse.isspmatrix_csr(X):
X = X.tocsr()
copy = False
if copy:
X = X.copy()
if self.scale_ is not None:
inplace_column_scale(X, self.scale_)
else:
X = np.asarray(X)
if copy:
X = X.copy()
if self.with_std:
X *= self.scale_
if self.with_mean:
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20 changes: 20 additions & 0 deletions sklearn/preprocessing/tests/test_data.py
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Expand Up @@ -750,6 +750,26 @@ def test_standard_scaler_trasform_with_partial_fit(sample_weight):
)


def test_standard_check_array_of_inverse_transform():
# Check if StandardScaler inverse_transform is
# converting the integer array to float
x = np.array([
[1, 1, 1, 0, 1, 0],
[1, 1, 1, 0, 1, 0],
[0, 8, 0, 1, 0, 0],
[1, 4, 1, 1, 0, 0],
[0, 1, 0, 0, 1, 0],
[0, 4, 0, 1, 0, 1]], dtype=np.int32)

scaler = StandardScaler()
scaler.fit(x)

# The of inverse_transform should be converted
# to a float array.
# If not X *= self.scale_ will fail.
scaler.inverse_transform(x)


def test_min_max_scaler_iris():
X = iris.data
scaler = MinMaxScaler()
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