title: "scoring must return a number" cross_val_score error in scikit-learn
body: <p>Maybe it is a dumb question, but I don't understand the error that the function <code>cross_val_score</code> in the code below give me. Perhaps the answer is in the format of <code>X</code> sample, seeing that this is exactly what was shown in the crash message, but I don't know how to fix.  This is a piece of code from my project with some random values.</p>
  
  <pre class="lang-py prettyprint-override"><code>import numpy as np
  from sklearn import mixture,cross_validation
  
  np.random.seed(0)
  n_samples = 300
  C = np.array([[0., -0.7], [3.5, .7]])
  X = np.r_[np.dot(np.random.randn(n_samples, 2), C),
            np.random.randn(n_samples, 2) + np.array([20, 20])]
  
  clf = mixture.GMM(n_components=2, covariance_type='full')
  score = cross_validation.cross_val_score(clf, X)
  </code></pre>
  
  <p>Gives me the error:</p>
  
  <pre><code>ValueError: scoring must return a number, got (&lt;type 'numpy.ndarray'&gt;) instead
  </code></pre>