title: Error when using scikit-learn to use pipelines
body: <p>I am trying to perform scaling using StandardScaler and define a KNeighborsClassifier(Create pipeline of scaler and estimator)</p>
  
  <p>Finally, I want to create a Grid Search cross validator for the above where param_grid will be a dictionary containing n_neighbors as hyperparameter and k_vals as values. </p>
  
  <pre><code>def kNearest(k_vals):
  
      skf = StratifiedKFold(n_splits=5, random_state=23)
  
      svp = Pipeline([('ss', StandardScaler()),
                  ('knc', neighbors.KNeighborsClassifier())])
  
      parameters = {'n_neighbors': k_vals}
  
      clf = GridSearchCV(estimator=svp, param_grid=parameters, cv=skf)
  
      return clf
  </code></pre>
  
  <p>But doing this will give me an error saying that</p>
  
  <pre><code>Invalid parameter n_neighbors for estimator Pipeline. Check the list of available parameters with `estimator.get_params().keys()`.
  </code></pre>
  
  <p>I've read the documentation, but still don't quite get what the error indicates and how to fix it.</p>