diff --git a/sklearn/covariance/_elliptic_envelope.py b/sklearn/covariance/_elliptic_envelope.py index 3ec1f855b3b08..b63a4a67a9cfd 100644 --- a/sklearn/covariance/_elliptic_envelope.py +++ b/sklearn/covariance/_elliptic_envelope.py @@ -41,7 +41,7 @@ class EllipticEnvelope(OutlierMixin, MinCovDet): random_state : int, RandomState instance or None, default=None Determines the pseudo random number generator for shuffling the data. Pass an int for reproducible results across multiple function - calls. See :term: `Glossary `. + calls. See :term:`Glossary `. Attributes ---------- diff --git a/sklearn/covariance/_robust_covariance.py b/sklearn/covariance/_robust_covariance.py index 22369d41bd97e..bd2232056c163 100644 --- a/sklearn/covariance/_robust_covariance.py +++ b/sklearn/covariance/_robust_covariance.py @@ -71,7 +71,7 @@ def c_step( random_state : int, RandomState instance or None, default=None Determines the pseudo random number generator for shuffling the data. Pass an int for reproducible results across multiple function calls. - See :term: `Glossary `. + See :term:`Glossary `. Returns ------- @@ -269,7 +269,7 @@ def select_candidates( random_state : int, RandomState instance or None, default=None Determines the pseudo random number generator for shuffling the data. Pass an int for reproducible results across multiple function calls. - See :term: `Glossary `. + See :term:`Glossary `. See Also --------- @@ -381,7 +381,7 @@ def fast_mcd( random_state : int, RandomState instance or None, default=None Determines the pseudo random number generator for shuffling the data. Pass an int for reproducible results across multiple function calls. - See :term: `Glossary `. + See :term:`Glossary `. Returns ------- @@ -610,7 +610,7 @@ class MinCovDet(EmpiricalCovariance): random_state : int, RandomState instance or None, default=None Determines the pseudo random number generator for shuffling the data. Pass an int for reproducible results across multiple function calls. - See :term: `Glossary `. + See :term:`Glossary `. Attributes ---------- diff --git a/sklearn/ensemble/_hist_gradient_boosting/binning.py b/sklearn/ensemble/_hist_gradient_boosting/binning.py index c76ee270b2270..af78372e6ceaa 100644 --- a/sklearn/ensemble/_hist_gradient_boosting/binning.py +++ b/sklearn/ensemble/_hist_gradient_boosting/binning.py @@ -115,7 +115,7 @@ class _BinMapper(TransformerMixin, BaseEstimator): Pseudo-random number generator to control the random sub-sampling. Pass an int for reproducible output across multiple function calls. - See :term: `Glossary `. + See :term:`Glossary `. n_threads : int, default=None Number of OpenMP threads to use. `_openmp_effective_n_threads` is called to determine the effective number of threads use, which takes cgroups CPU diff --git a/sklearn/gaussian_process/_gpc.py b/sklearn/gaussian_process/_gpc.py index 5e7fe0a542b55..fe4bec5dca1c2 100644 --- a/sklearn/gaussian_process/_gpc.py +++ b/sklearn/gaussian_process/_gpc.py @@ -110,7 +110,7 @@ def optimizer(obj_func, initial_theta, bounds): random_state : int, RandomState instance or None, default=None Determines random number generation used to initialize the centers. Pass an int for reproducible results across multiple function calls. - See :term: `Glossary `. + See :term:`Glossary `. Attributes ---------- @@ -559,7 +559,7 @@ def optimizer(obj_func, initial_theta, bounds): random_state : int, RandomState instance or None, default=None Determines random number generation used to initialize the centers. Pass an int for reproducible results across multiple function calls. - See :term: `Glossary `. + See :term:`Glossary `. multi_class : {'one_vs_rest', 'one_vs_one'}, default='one_vs_rest' Specifies how multi-class classification problems are handled. diff --git a/sklearn/inspection/_permutation_importance.py b/sklearn/inspection/_permutation_importance.py index f94219e7d6190..b095cbec9ee49 100644 --- a/sklearn/inspection/_permutation_importance.py +++ b/sklearn/inspection/_permutation_importance.py @@ -171,7 +171,7 @@ def permutation_importance( Pseudo-random number generator to control the permutations of each feature. Pass an int to get reproducible results across function calls. - See :term: `Glossary `. + See :term:`Glossary `. sample_weight : array-like of shape (n_samples,), default=None Sample weights used in scoring. diff --git a/sklearn/manifold/_locally_linear.py b/sklearn/manifold/_locally_linear.py index 6da9d01b64f9f..73360bf07275f 100644 --- a/sklearn/manifold/_locally_linear.py +++ b/sklearn/manifold/_locally_linear.py @@ -154,7 +154,7 @@ def null_space( random_state : int, RandomState instance, default=None Determines the random number generator when ``solver`` == 'arpack'. Pass an int for reproducible results across multiple function calls. - See :term: `Glossary `. + See :term:`Glossary `. """ if eigen_solver == "auto": if M.shape[0] > 200 and k + k_skip < 10: @@ -268,7 +268,7 @@ def locally_linear_embedding( random_state : int, RandomState instance, default=None Determines the random number generator when ``solver`` == 'arpack'. Pass an int for reproducible results across multiple function calls. - See :term: `Glossary `. + See :term:`Glossary `. n_jobs : int or None, default=None The number of parallel jobs to run for neighbors search. @@ -608,7 +608,7 @@ class LocallyLinearEmbedding(TransformerMixin, _UnstableArchMixin, BaseEstimator random_state : int, RandomState instance, default=None Determines the random number generator when ``eigen_solver`` == 'arpack'. Pass an int for reproducible results - across multiple function calls. See :term: `Glossary `. + across multiple function calls. See :term:`Glossary `. n_jobs : int or None, default=None The number of parallel jobs to run. diff --git a/sklearn/manifold/_mds.py b/sklearn/manifold/_mds.py index fb2fe3d3da9b8..6fd9fbcd1308f 100644 --- a/sklearn/manifold/_mds.py +++ b/sklearn/manifold/_mds.py @@ -61,7 +61,7 @@ def _smacof_single( random_state : int, RandomState instance or None, default=None Determines the random number generator used to initialize the centers. Pass an int for reproducible results across multiple function calls. - See :term: `Glossary `. + See :term:`Glossary `. Returns ------- @@ -220,7 +220,7 @@ def smacof( random_state : int, RandomState instance or None, default=None Determines the random number generator used to initialize the centers. Pass an int for reproducible results across multiple function calls. - See :term: `Glossary `. + See :term:`Glossary `. return_n_iter : bool, default=False Whether or not to return the number of iterations. @@ -347,7 +347,7 @@ class MDS(BaseEstimator): random_state : int, RandomState instance or None, default=None Determines the random number generator used to initialize the centers. Pass an int for reproducible results across multiple function calls. - See :term: `Glossary `. + See :term:`Glossary `. dissimilarity : {'euclidean', 'precomputed'}, default='euclidean' Dissimilarity measure to use: diff --git a/sklearn/manifold/_t_sne.py b/sklearn/manifold/_t_sne.py index 2cb1369b6cf0f..738f3847c94b3 100644 --- a/sklearn/manifold/_t_sne.py +++ b/sklearn/manifold/_t_sne.py @@ -619,7 +619,7 @@ class TSNE(BaseEstimator): Determines the random number generator. Pass an int for reproducible results across multiple function calls. Note that different initializations might result in different local minima of the cost - function. See :term: `Glossary `. + function. See :term:`Glossary `. method : str, default='barnes_hut' By default the gradient calculation algorithm uses Barnes-Hut diff --git a/sklearn/neighbors/_kde.py b/sklearn/neighbors/_kde.py index 66c4a652d5441..c15c79c73e680 100644 --- a/sklearn/neighbors/_kde.py +++ b/sklearn/neighbors/_kde.py @@ -281,7 +281,7 @@ def sample(self, n_samples=1, random_state=None): Determines random number generation used to generate random samples. Pass an int for reproducible results across multiple function calls. - See :term: `Glossary `. + See :term:`Glossary `. Returns -------