warning conventions
@@ -929,6 +929,10 @@ def non_negative_factorization(
The objective function is minimized with an alternating minimization of W
and H. If H is given and update_H=False, it solves for W only.
+ Note that the transformed data is named W and the components matrix is named H. In
+ the NMF literature, the naming convention is usually the opposite since the data
+ matrix X is transposed.
+
Parameters
----------
X : array-like of shape (n_samples, n_features)
@@ -1151,6 +1155,10 @@ class NMF(_ClassNamePrefixFeaturesOutMixin, TransformerMixin, BaseEstimator):
The objective function is minimized with an alternating minimization of W
and H.
+ Note that the transformed data is named W and the components matrix is named H. In
+ the NMF literature, the naming convention is usually the opposite since the data
+ matrix X is transposed.
+
Read more in the :ref:`User Guide <NMF>`.
Parameters
