DOC Fix doc of defaults in sklearn.manifold._mds.py
@@ -19,7 +19,7 @@ from ..utils.validation import _deprecate_positional_args
def _smacof_single(dissimilarities, metric=True, n_components=2, init=None,
max_iter=300, verbose=0, eps=1e-3, random_state=None):
- """Computes multidimensional scaling using SMACOF algorithm
+ """Computes multidimensional scaling using SMACOF algorithm.
Parameters
----------
@@ -158,7 +158,7 @@ def smacof(dissimilarities, *, metric=True, n_components=2, init=None,
dissimilarities : ndarray of shape (n_samples, n_samples)
Pairwise dissimilarities between the points. Must be symmetric.
- metric : boolean, optional, default: True
+ metric : bool, default=True
Compute metric or nonmetric SMACOF algorithm.
n_components : int, default=2
@@ -275,7 +275,7 @@ def smacof(dissimilarities, *, metric=True, n_components=2, init=None,
class MDS(BaseEstimator):
- """Multidimensional scaling
+ """Multidimensional scaling.
Read more in the :ref:`User Guide <multidimensional_scaling>`.
@@ -390,7 +390,7 @@ class MDS(BaseEstimator):
def fit(self, X, y=None, init=None):
"""
- Computes the position of the points in the embedding space
+ Computes the position of the points in the embedding space.
Parameters
----------
@@ -411,7 +411,7 @@ class MDS(BaseEstimator):
def fit_transform(self, X, y=None, init=None):
"""
- Fit the data from X, and returns the embedded coordinates
+ Fit the data from X, and returns the embedded coordinates.
Parameters
----------
