title: SGDClassifier kernel dies when using scikit
body: <p>I tried this very simple example</p>
  
  <pre><code>import numpy as np
  from sklearn import linear_model
  X = np.array([[-1, -1], [-2, -1], [1, 1], [2, 1]])
  Y = np.array([1, 1, 2, 2])
  clf = linear_model.SGDClassifier()
  clf.fit(X, Y)
  </code></pre>
  
  <p>but the Kernel dies immediately </p>
  
  <pre><code>Kernel died, restarting
  </code></pre>
  
  <p>Fitting a Random Forest works without problem:</p>
  
  <pre><code>from sklearn import ensemble
  clf2 = ensemble.RandomForestClassifier()
  clf2.fit(X, Y)
  </code></pre>
  
  <p>I have no idea why this occurs. I am using the current version of anaconda3 with all updates on a ubuntu 16.04 64bit system.</p>
  
  <p>UPDATE: I just found that this happens with all model from the <code>linear_model</code> class</p>
  
  <p>UPDATE2: MKL was the problem, as described here: <a href="https://github.com/scikit-learn/scikit-learn/issues/5046" rel="nofollow">https://github.com/scikit-learn/scikit-learn/issues/5046</a></p>
  
  <p>and <code>conda install nomkl</code> fixed it.</p>