scikit-learn
diff --git a/‎doc/whats_new/v1.1.rst
Lines changed: 4 additions & 0 deletions b/‎doc/whats_new/v1.1.rst
Lines changed: 4 additions & 0 deletions
diff --git a/‎sklearn/base.py
Lines changed: 4 additions & 5 deletions b/‎sklearn/base.py
Lines changed: 4 additions & 5 deletions
diff --git a/‎sklearn/tests/test_pipeline.py
Lines changed: 17 additions & 6 deletions b/‎sklearn/tests/test_pipeline.py
Lines changed: 17 additions & 6 deletions
@@ -45,6 +45,10 @@ Changelog
   message suggests potential solutions.
   :pr:`21219` by :user:`Olivier Grisel <ogrisel>`.
 
+- |Enhancement| All scikit-learn models now generate a more informative
+  error message when setting invalid hyper-parameters with `set_params`.
+  :pr:`21542` by :user:`Olivier Grisel <ogrisel>`.
+
 :mod:`sklearn.calibration`
 ..........................
 
 
@@ -212,8 +212,7 @@ def get_params(self, deep=True):
         return out
 
     def set_params(self, **params):
-        """
-        Set the parameters of this estimator.
+        """Set the parameters of this estimator.
 
         The method works on simple estimators as well as on nested objects
         (such as :class:`~sklearn.pipeline.Pipeline`). The latter have
@@ -239,10 +238,10 @@ def set_params(self, **params):
         for key, value in params.items():
             key, delim, sub_key = key.partition("__")
             if key not in valid_params:
+                local_valid_params = self._get_param_names()
                 raise ValueError(
-                    "Invalid parameter %s for estimator %s. "
-                    "Check the list of available parameters "
-                    "with `estimator.get_params().keys()`." % (key, self)
+                    f"Invalid parameter {key!r} for estimator {self}. "
+                    f"Valid parameters are: {local_valid_params!r}."
                 )
 
             if delim:
 
@@ -216,7 +216,10 @@ def test_pipeline_init():
     repr(pipe)
 
     # Check that params are not set when naming them wrong
-    msg = "Invalid parameter C for estimator SelectKBest"
+    msg = re.escape(
+        "Invalid parameter 'C' for estimator SelectKBest(). Valid parameters are: ['k',"
+        " 'score_func']."
+    )
     with pytest.raises(ValueError, match=msg):
         pipe.set_params(anova__C=0.1)
 
@@ -316,18 +319,26 @@ def test_pipeline_raise_set_params_error():
 
     # expected error message
     error_msg = re.escape(
-        f"Invalid parameter fake for estimator {pipe}. "
-        "Check the list of available parameters "
-        "with `estimator.get_params().keys()`."
+        "Invalid parameter 'fake' for estimator Pipeline(steps=[('cls',"
+        " LinearRegression())]). Valid parameters are: ['memory', 'steps', 'verbose']."
     )
-
     with pytest.raises(ValueError, match=error_msg):
         pipe.set_params(fake="nope")
 
-    # nested model check
+    # invalid outer parameter name for compound parameter: the expected error message
+    # is the same as above.
     with pytest.raises(ValueError, match=error_msg):
         pipe.set_params(fake__estimator="nope")
 
+    # expected error message for invalid inner parameter
+    error_msg = re.escape(
+        "Invalid parameter 'invalid_param' for estimator LinearRegression(). Valid"
+        " parameters are: ['copy_X', 'fit_intercept', 'n_jobs', 'normalize',"
+        " 'positive']."
+    )
+    with pytest.raises(ValueError, match=error_msg):
+        pipe.set_params(cls__invalid_param="nope")
+
 
 def test_pipeline_methods_pca_svm():
     # Test the various methods of the pipeline (pca + svm).