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FIX Error for sparse matrix in OrdinalEncoder.inverse_transform #19879

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Merged
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Apr 13, 2021
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FIX Error for sparse matrix in OrdinalEncoder.inverse_transform #19879

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325e62e
FIX do not support sparse matrix in OrdinalEncoder.inverse_transform
glemaitre Apr 13, 2021
8a78ef9
solve conflict
glemaitre Apr 13, 2021
6295650
whats new
glemaitre Apr 13, 2021
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4 changes: 4 additions & 0 deletions doc/whats_new/v1.0.rst
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Expand Up @@ -343,6 +343,10 @@ Changelog
`handle_unknown='ignore'` and dropping categories. :pr:`19041` by
`Thomas Fan`_.

- |Fix| :meth:`preprocessing.OrdinalEncoder.inverse_transform` is not
supporting sparse matrix and raise the appropriate error message.
:pr:`19879` by :user:`Guillaume Lemaitre <glemaitre>`.

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

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4 changes: 2 additions & 2 deletions sklearn/preprocessing/_encoders.py
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Expand Up @@ -846,7 +846,7 @@ def inverse_transform(self, X):

Parameters
----------
X : {array-like, sparse matrix} of shape (n_samples, n_features)
X : array-like of shape (n_samples, n_encoded_features)
The transformed data.

Returns
Expand All @@ -855,7 +855,7 @@ def inverse_transform(self, X):
Inverse transformed array.
"""
check_is_fitted(self)
X = check_array(X, accept_sparse='csr', force_all_finite='allow-nan')
X = check_array(X, force_all_finite='allow-nan')

n_samples, _ = X.shape
n_features = len(self.categories_)
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22 changes: 22 additions & 0 deletions sklearn/preprocessing/tests/test_encoders.py
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Expand Up @@ -1110,3 +1110,25 @@ def test_ordinal_encoder_handle_missing_and_unknown(
assert_allclose(X_trans, expected_X_trans)

assert_allclose(oe.transform(X_test), [[-1.0]])


def test_ordinal_encoder_sparse():
"""Check that we raise proper error with sparse input in OrdinalEncoder.
Non-regression test for:
https://github.com/scikit-learn/scikit-learn/issues/19878
"""
X = np.array([[3, 2, 1], [0, 1, 1]])
X_sparse = sparse.csr_matrix(X)

encoder = OrdinalEncoder()

err_msg = "A sparse matrix was passed, but dense data is required"
with pytest.raises(TypeError, match=err_msg):
encoder.fit(X_sparse)
with pytest.raises(TypeError, match=err_msg):
encoder.fit_transform(X_sparse)

X_trans = encoder.fit_transform(X)
X_trans_sparse = sparse.csr_matrix(X_trans)
with pytest.raises(TypeError, match=err_msg):
encoder.inverse_transform(X_trans_sparse)