title: python sklearn GradientBoostingClassifier warm start error
body: <p>I've used the model to train a classifier on a set of data with 1000 iterations:</p>
  
  <pre><code>clf = GradientBoostingClassifier(n_estimators=1000, learning_rate=0.05, subsample=0.1, max_depth=3)
  clf.fit(X, y, sample_weight=train_weight)
  </code></pre>
  
  <p>Now I want to increase the number of iterations to 2000. So I do:</p>
  
  <pre><code>clf.set_params(n_estimators=2000, warm_start=True)
  clf.fit(X, y, sample_weight=train_weight)
  </code></pre>
  
  <p>But I get the following error:</p>
  
  <pre><code>---------------------------------------------------------------------------
  ValueError                                Traceback (most recent call last)
  &lt;ipython-input-13-49cfdfd6c024&gt; in &lt;module&gt;()
  
        1 start = time.clock()
        2 clf.set_params(n_estimators=2000, warm_start=True)
  ----&gt; 3 clf.fit(X, y, sample_weight=train_weight)
        4 ...
  
  C:\Anaconda3\lib\site-packages\sklearn\ensemble\gradient_boosting.py in fit(self, X, y, sample_weight, monitor)
     1002                                     self.estimators_.shape[0]))
     1003             begin_at_stage = self.estimators_.shape[0]
  -&gt; 1004             y_pred = self._decision_function(X)
     1005             self._resize_state()
     1006 
  
  C:\Anaconda3\lib\site-packages\sklearn\ensemble\gradient_boosting.py in _decision_function(self, X)
     1120         # not doing input validation.
     1121         score = self._init_decision_function(X)
  -&gt; 1122         predict_stages(self.estimators_, X, self.learning_rate, score)
     1123         return score
     1124 
  
  sklearn/ensemble/_gradient_boosting.pyx in sklearn.ensemble._gradient_boosting.predict_stages (sklearn\ensemble\_gradient_boosting.c:2564)()
  
  ValueError: ndarray is not C-contiguous
  </code></pre>
  
  <p>What am I doing wrong here?</p>