title: Does including a scaler in sklearn's Pipeline scale the target variable?
body: <p>When using a scaling function in  <code>sklearn</code>'s Pipeline utility, is the scalar applied to the target variable during training and prediction?</p>
  
  <p>In other words, is my code below, which makes use of <code>TransformedTargetRegressor</code> redundant to the pipeline?</p>
  
  <pre><code>cowboy = Lasso(max_iter=10000, tol=.005)
  climber = Ridge()
  gymshorts = ElasticNet()
  scaler = pre.RobustScaler()
  
  models = [('xgb', xgb.XGBRegressor(**best_params)),
            ('ridge', make_pipeline(scaler, TransformedTargetRegressor(climber, scaler))),
            ('lasso', make_pipeline(scaler, TransformedTargetRegressor(cowboy, scaler))),
            ('enet', make_pipeline(scaler, TransformedTargetRegressor(gymshorts, scaler)))]
  
  stack = ensemble.StackingRegressor(estimators=models)
  stack = stack.fit(x_train, y_train)
  </code></pre>