DOC removed algorithm parameter of CCA (scikit-learn#19047)

Author: NicolasHug

sklearn/cross_decomposition/_pls.py

@@ -700,14 +700,8 @@ class CCA(_PLS):
     scale : bool, default=True
         Whether to scale `X` and `Y`.
 
-    algorithm : {'nipals', 'svd'}, default='nipals'
-        The algorithm used to estimate the first singular vectors of the
-        cross-covariance matrix. 'nipals' uses the power method while 'svd'
-        will compute the whole SVD.
-
     max_iter : int, default=500
-        the maximum number of iterations of the power method when
-        `algorithm='nipals'`. Ignored otherwise.
+        the maximum number of iterations of the power method.
 
     tol : real, default 1e-06
         The tolerance used as convergence criteria in the power method: the
@@ -763,7 +757,7 @@ class CCA(_PLS):
 
     n_iter_ : list of shape (n_components,)
         Number of iterations of the power method, for each
-        component. Empty if `algorithm='svd'`.
+        component.
 
     Examples
     --------