DOC Added meaning of default=None for n_components in MiniBatchSparsePCA and MiniBatchDictionaryLearning (#21428)

alceballosa · web-flow · commit d742a58b9df9 · 2021-10-25T17:41:27.000+02:00
diff --git a/sklearn/decomposition/_dict_learning.py b/sklearn/decomposition/_dict_learning.py
@@ -762,8 +762,9 @@ def dict_learning_online(
     X : ndarray of shape (n_samples, n_features)
         Data matrix.
 
-    n_components : int, default=2
-        Number of dictionary atoms to extract.
+    n_components : int or None, default=2
+        Number of dictionary atoms to extract. If None, then ``n_components``
+        is set to ``n_features``.
 
     alpha : float, default=1
         Sparsity controlling parameter.
@@ -1335,8 +1336,9 @@ class DictionaryLearning(_BaseSparseCoding, BaseEstimator):
 
     Parameters
     ----------
-    n_components : int, default=n_features
-        Number of dictionary elements to extract.
+    n_components : int, default=None
+        Number of dictionary elements to extract. If None, then ``n_components``
+        is set to ``n_features``.
 
     alpha : float, default=1.0
         Sparsity controlling parameter.
diff --git a/sklearn/decomposition/_sparse_pca.py b/sklearn/decomposition/_sparse_pca.py
@@ -24,7 +24,7 @@ class SparsePCA(TransformerMixin, BaseEstimator):
     ----------
     n_components : int, default=None
         Number of sparse atoms to extract. If None, then ``n_components``
-        is set to ``n_features_in_``.
+        is set to ``n_features``.
 
     alpha : float, default=1
         Sparsity controlling parameter. Higher values lead to sparser
@@ -249,7 +249,8 @@ class MiniBatchSparsePCA(SparsePCA):
     Parameters
     ----------
     n_components : int, default=None
-        Number of sparse atoms to extract.
+        Number of sparse atoms to extract. If None, then ``n_components``
+        is set to ``n_features``.
 
     alpha : int, default=1
         Sparsity controlling parameter. Higher values lead to sparser
