10000 MAINT Parameters validation for sklearn.metrics.pairwise.sigmoid_kern… · scikit-learn/scikit-learn@db83e23 · GitHub
[go: up one dir, main page]

Skip to content

Commit db83e23

Browse files
MAINT Parameters validation for sklearn.metrics.pairwise.sigmoid_kernel (#26072)
Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>
1 parent d431aa6 commit db83e23

File tree

2 files changed

+15
-2
lines changed

2 files changed

+15
-2
lines changed

sklearn/metrics/pairwise.py

+14-2
Original file line numberDiff line numberDiff line change
@@ -1290,6 +1290,18 @@ def polynomial_kernel(X, Y=None, degree=3, gamma=None, coef0=1):
12901290
return K
12911291

12921292

1293+
@validate_params(
1294+
{
1295+
"X": ["array-like", "sparse matrix"],
1296+
"Y": ["array-like", "sparse matrix", None],
1297+
"gamma": [
1298+
Interval(Real, 0, None, closed="left"),
1299+
None,
1300+
Hidden(np.ndarray),
1301+
],
1302+
"coef0": [Interval(Real, None, None, closed="neither")],
1303+
}
1304+
)
12931305
def sigmoid_kernel(X, Y=None, gamma=None, coef0=1):
12941306
"""Compute the sigmoid kernel between X and Y.
12951307
@@ -1299,10 +1311,10 @@ def sigmoid_kernel(X, Y=None, gamma=None, coef0=1):
12991311
13001312
Parameters
13011313
----------
1302-
X : ndarray of shape (n_samples_X, n_features)
1314+
X : {array-like, sparse matrix} of shape (n_samples_X, n_features)
13031315
A feature array.
13041316
1305-
Y : ndarray of shape (n_samples_Y, n_features), default=None
1317+
Y : {array-like, sparse matrix} of shape (n_samples_Y, n_features), default=None
13061318
An optional second feature array. If `None`, uses `Y=X`.
13071319
13081320
gamma : float, default=None

sklearn/tests/test_public_functions.py

+1
Original file line numberDiff line numberDiff line change
@@ -217,6 +217,7 @@ def _check_function_param_validation(
217217
"sklearn.metrics.pairwise.paired_manhattan_distances",
218218
"sklearn.metrics.pairwise.polynomial_kernel",
219219
"sklearn.metrics.pairwise.rbf_kernel",
220+
"sklearn.metrics.pairwise.sigmoid_kernel",
220221
"sklearn.metrics.precision_recall_curve",
221222
"sklearn.metrics.precision_recall_fscore_support",
222223
"sklearn.metrics.precision_score",

0 commit comments

Comments
 (0)
0