title: RandomForestClassifier object has no attribute 'estimators'
body: <p>I am trying to run GridsearchCV on few classification model in order to optimize them. My code is as follows:</p>
  
  <pre><code>models = ['Random Forest','KNN','Decision Tree'] 
  classifiers ={RandomForestClassifier(random_state=3):{"max_depth": 
  [2,3,4,5,6,7,8,9,10,11,12]
          ,"min_samples_split" :[2,3,4,5,6]
          ,"n_estimators" : [10]
          ,"min_samples_leaf": [1,2,3,4,5]
          ,"max_features": (4,5,6,"sqrt")
          ,"criterion": ('gini','entropy')},
  KNeighborsClassifier():{'n_neighbors':range(15,30), 
            'p':[1,2],
            'weights':['uniform','distance']}
  }
  
  class_names = list(y_lab.values)
  for model, classifier in zip(models,classifiers.keys()):
          clf = GridSearchCV(estimator = classifier,param_grid = 
  classifier[classifier],cv=5, scoring="roc_auc", n_jobs= -1)
          clf.fit(X_train, y_train)
          print ('For model %s' %model+ ', the cross valudation score is %.5f'% 
  clf.best_score_)  
          y_pred = clf.best_estimator_.predict(X_test)
          print ('The accuracy score for the model %s' % model + 'is %.5f' + 
  accuracy_score(y_pred,y_test))
          cm = confusionMatrix(y_pred,y_test)
  </code></pre>
  
  <p>Yet, the outcome yields:
  AttributeError: 'RandomForestClassifier' object has no attribute 'estimators_'
  This code pattern has worked before, but no idea what causes this error message</p>