title: Random Forest with GridSearchCV - Error on param_grid
body: <p>Im trying to create a Random Forest model with GridSearchCV but am getting an error pertaining to param_grid: <em>"ValueError: Invalid parameter max_features for estimator Pipeline. Check the list of available parameters with `estimator.get_params().keys()"</em>. I'm classifying documents so I am also pushing tf-idf vectorizer to the pipeline.
  Here is the code:</p>
  
  <pre><code>from sklearn import metrics
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.metrics import classification_report, f1_score, accuracy_score, precision_score, confusion_matrix
  from sklearn.pipeline import Pipeline
  
   #Classifier Pipeline
  pipeline = Pipeline([
      ('tfidf', TfidfVectorizer()),
      ('classifier', RandomForestClassifier())
  ])
  # Params for classifier
  params = {"max_depth": [3, None],
                "max_features": [1, 3, 10],
                "min_samples_split": [1, 3, 10],
                "min_samples_leaf": [1, 3, 10],
                # "bootstrap": [True, False],
                "criterion": ["gini", "entropy"]}
  
  # Grid Search Execute
  rf_grid = GridSearchCV(estimator=pipeline , param_grid=params) #cv=10
  rf_detector = rf_grid.fit(X_train, Y_train)
  print(rf_grid.grid_scores_)
  </code></pre>
  
  <p>I can't figure out why the error is showing. The same btw is occurring when I run a decision tree with GridSearchCV. (Scikit-learn 0.17)</p>