[DOC] Improved consistency of the docstring of an ignored y parameter (scikit-learn#19049)

Author: rohan-paul

sklearn/covariance/_empirical_covariance.py

@@ -196,7 +196,7 @@ def fit(self, X, y=None):
           n_features is the number of features.
 
         y : Ignored
-            Not used, present for API consistence purpose.
+            Not used, present for API consistency by convention.
 
         Returns
         -------
@@ -226,7 +226,7 @@ def score(self, X_test, y=None):
             the data used in fit (including centering).
 
         y : Ignored
-            Not used, present for API consistence purpose.
+            Not used, present for API consistency by convention.
 
         Returns
         -------

sklearn/covariance/_graph_lasso.py

@@ -386,7 +386,7 @@ def fit(self, X, y=None):
             Data from which to compute the covariance estimate
 
         y : Ignored
-            Not used, present for API consistence purpose.
+            Not used, present for API consistency by convention.
 
         Returns
         -------
@@ -696,7 +696,7 @@ def fit(self, X, y=None):
             Data from which to compute the covariance estimate
 
         y : Ignored
-            Not used, present for API consistence purpose.
+            Not used, present for API consistency by convention.
 
         Returns
         -------

sklearn/covariance/_robust_covariance.py

@@ -633,7 +633,7 @@ def fit(self, X, y=None):
             and `n_features` is the number of features.
 
         y: Ignored
-            Not used, present for API consistence purpose.
+            Not used, present for API consistency by convention.
 
         Returns
         -------

sklearn/covariance/_shrunk_covariance.py

@@ -136,7 +136,7 @@ def fit(self, X, y=None):
             and n_features is the number of features.
 
         y: Ignored
-            not used, present for API consistence purpose.
+            Not used, present for API consistency by convention.
 
         Returns
         -------
@@ -408,7 +408,7 @@ def fit(self, X, y=None):
             Training data, where `n_samples` is the number of samples
             and `n_features` is the number of features.
         y : Ignored
-            not used, present for API consistence purpose.
+            Not used, present for API consistency by convention.
 
         Returns
         -------
@@ -584,7 +584,7 @@ def fit(self, X, y=None):
             Training data, where `n_samples` is the number of samples
             and `n_features` is the number of features.
         y : Ignored
-            not used, present for API consistence purpose.
+            Not used, present for API consistency by convention.
 
         Returns
         -------