title: return coefficients from Pipeline object in sklearn
body: <p>I've fit a <code>Pipeline</code> object with <code>RandomizedSearchCV</code></p>
  
  <pre><code>pipe_sgd = Pipeline([('scl', StandardScaler()),
                      ('clf', SGDClassifier(n_jobs=-1))])
  
  param_dist_sgd = {'clf__loss': ['log'],
                   'clf__penalty': [None, 'l1', 'l2', 'elasticnet'],
                   'clf__alpha': np.linspace(0.15, 0.35),
                   'clf__n_iter': [3, 5, 7]}
  
  sgd_randomized_pipe = RandomizedSearchCV(estimator = pipe_sgd, 
                                           param_distributions=param_dist_sgd, 
                                           cv=3, n_iter=30, n_jobs=-1)
  
  sgd_randomized_pipe.fit(X_train, y_train)
  </code></pre>
  
  <p>I want to access the <code>coef_</code> attribute of the <code>best_estimator_</code> but I'm unable to do that. I've tried accessing <code>coef_</code> with the code below.</p>
  
  <p><code>sgd_randomized_pipe.best_estimator_.coef_</code></p>
  
  <p>However I get the following AttributeError... </p>
  
  <p>AttributeError: 'Pipeline' object has no attribute 'coef_'</p>
  
  <p>The scikit-learn docs say that <code>coef_</code> is an attribute of <code>SGDClassifier</code>, which is the class of my <code>base_estimator_</code>. </p>
  
  <p>What am I doing wrong?</p>