title: memory error when todense in python using CountVectorizer
body: <p>Here is my code and memory error when call <code>todense()</code>, I am using GBDT model, and wondering if anyone have good ideas how to work around memory error? Thanks.</p>
  
  <pre><code>  for feature_colunm_name in feature_columns_to_use:
      X_train[feature_colunm_name] = CountVectorizer().fit_transform(X_train[feature_colunm_name]).todense()
      X_test[feature_colunm_name] = CountVectorizer().fit_transform(X_test[feature_colunm_name]).todense()
    y_train = y_train.astype('int')
    grd = GradientBoostingClassifier(n_estimators=n_estimator, max_depth=10)
    grd.fit(X_train.values, y_train.values)
  </code></pre>
  
  <p>Detailed error message,</p>
  
  <pre><code>in _process_toarray_args
      return np.zeros(self.shape, dtype=self.dtype, order=order)
  MemoryError
  ...
  </code></pre>
  
  <p>regards,
  Lin</p>