scikit-learn · jeremiedbb · Jan 12, 2021 · Jan 11, 2021
diff --git a/sklearn/cross_decomposition/_pls.py b/sklearn/cross_decomposition/_pls.py
@@ -499,7 +499,7 @@ class PLSRegression(_PLS):
         The maximum number of iterations of the power method when
         `algorithm='nipals'`. Ignored otherwise.
 
-    tol : real, default 1e-06
+    tol : float, default=1e-06
         The tolerance used as convergence criteria in the power method: the
         algorithm stops whenever the squared norm of `u_i - u_{i-1}` is less
         than `tol`, where `u` corresponds to the left singular vector.
@@ -597,7 +597,7 @@ class PLSCanonical(_PLS):
         the maximum number of iterations of the power method when
         `algorithm='nipals'`. Ignored otherwise.
 
-    tol : real, default 1e-06
+    tol : float, default=1e-06
         The tolerance used as convergence criteria in the power method: the
         algorithm stops whenever the squared norm of `u_i - u_{i-1}` is less
         than `tol`, where `u` corresponds to the left singular vector.
@@ -703,7 +703,7 @@ class CCA(_PLS):
     max_iter : int, default=500
         the maximum number of iterations of the power method.
 
-    tol : real, default 1e-06
+    tol : float, default=1e-06
         The tolerance used as convergence criteria in the power method: the
         algorithm stops whenever the squared norm of `u_i - u_{i-1}` is less
         than `tol`, where `u` corresponds to the left singular vector.