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MAINT Parameters validation for additive_chi2_kernel #25424

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merged 2 commits into from
Jan 24, 2023
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MAINT Parameters validation for additive_chi2_kernel #25424

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847cd9f
MAINT Parameters validation for metrics.pairwise.additive_chi2_kernel
yuanx749 Jan 18, 2023
49afc48
Merge branch 'main' into validate_additive_chi2_kernel
glemaitre Jan 24, 2023
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6 changes: 3 additions & 3 deletions sklearn/metrics/pairwise.py
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Original file line number Diff line number Diff line change
Expand Up @@ -29,6 +29,7 @@
from ..utils._mask import _get_mask
from ..utils.parallel import delayed, Parallel
from ..utils.fixes import sp_version, parse_version
from ..utils._param_validation import validate_params

from ._pairwise_distances_reduction import ArgKmin
from ._pairwise_fast import _chi2_kernel_fast, _sparse_manhattan
Expand Down Expand Up @@ -1403,6 +1404,7 @@ def cosine_similarity(X, Y=None, dense_output=True):
return K


@validate_params({"X": ["array-like"], "Y": ["array-like", None]})
def additive_chi2_kernel(X, Y=None):
"""Compute the additive chi-squared kernel between observations in X and Y.

Expand All @@ -1423,7 +1425,7 @@ def additive_chi2_kernel(X, Y=None):
X : array-like of shape (n_samples_X, n_features)
A feature array.

Y : ndarray of shape (n_samples_Y, n_features), default=None
Y : array-like of shape (n_samples_Y, n_features), default=None
An optional second feature array. If `None`, uses `Y=X`.

Returns
Expand Down Expand Up @@ -1451,8 +1453,6 @@ def additive_chi2_kernel(X, Y=None):
International Journal of Computer Vision 2007
https://hal.archives-ouvertes.fr/hal-00171412/document
"""
if issparse(X) or issparse(Y):
raise ValueError("additive_chi2 does not support sparse matrices.")
X, Y = check_pairwise_arrays(X, Y)
if (X < 0).any():
raise ValueError("X contains negative values.")
Expand Down
8 changes: 0 additions & 8 deletions sklearn/metrics/tests/test_pairwise.py
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Expand Up @@ -390,8 +390,6 @@ def test_pairwise_kernels(metric):
Y_sparse = csr_matrix(Y)
if metric in ["chi2", "additive_chi2"]:
# these don't support sparse matrices yet
with pytest.raises(ValueError):
pairwise_kernels(X_sparse, Y=Y_sparse, metric=metric)
return
K1 = pairwise_kernels(X_sparse, Y=Y_sparse, metric=metric)
assert_allclose(K1, K2)
Expand Down Expand Up @@ -1231,12 +1229,6 @@ def test_chi_square_kernel():
with pytest.raises(ValueError):
chi2_kernel([[0, 1]], [[0.2, 0.2, 0.6]])

# sparse matrices
with pytest.raises(ValueError):
chi2_kernel(csr_matrix(X), csr_matrix(Y))
with pytest.raises(ValueError):
additive_chi2_kernel(csr_matrix(X), csr_matrix(Y))


@pytest.mark.parametrize(
"kernel",
Expand Down
1 change: 1 addition & 0 deletions sklearn/tests/test_public_functions.py
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Expand Up @@ -122,6 +122,7 @@ def _check_function_param_validation(
"sklearn.metrics.median_absolute_error",
"sklearn.metrics.multilabel_confusion_matrix",
"sklearn.metrics.mutual_info_score",
"sklearn.metrics.pairwise.additive_chi2_kernel",
"sklearn.metrics.r2_score",
"sklearn.metrics.roc_curve",
"sklearn.metrics.zero_one_loss",
Expand Down