title: gridsearchCV for linear regression
body: <p>I am having a difficult using gridCVsearch code for different linear models.</p>
  <p>I get errors at the same stage for each model.
  For example, my codes for Linear Regression is as below:</p>
  <pre><code>from sklearn.model_selection import GridSearchCV
  from sklearn.linear_model import LinearRegression
  from sklearn.pipeline import make_pipeline
  lr_pipe = make_pipeline(StandardScaler(), LinearRegression())
  lr_pipe.fit(X_train, y_train)
  lr_pipe.score(X_test, y_test)
  param_grid = {'n_neighbors': range(1, 10)}
  grid = GridSearchCV(lr_pipe, param_grid, cv=10)
  grid.fit(X_train, y_train)
  print(grid.best_params_)
  print(grid.score(X_test, y_test))
  </code></pre>
  <p>I get error at the step &quot;grid.fit(X_train, y_train)&quot; with a message:</p>
  <pre><code>ValueError: Invalid parameter n_neighbors for estimator Pipeline(memory=None,
       steps=[('standardscaler',
               StandardScaler(copy=True, with_mean=True, with_std=True)),
              ('linearregression',
               LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None,
                                normalize=False))],
       verbose=False). Check the list of available parameters with `estimator.get_params().keys()`.
  </code></pre>
  <p>What did i do wrong in my coding? i followed exactly the general codings for gridsearchCV.</p>