title: Fitting Naive Bayes on Floating Point Data Values
body: <p>I want to fit Gaussian Naive Bayes on data values with floating point, and the code I'm using is this:</p>
  
  <pre><code>array1 = np.array([[2,2],[3,2]]) 
  array2 = np.array([0.3,3])
  
  clf = GaussianNB()
  clf.fit(array1,array2)
  </code></pre>
  
  <p>But, I get an error saying:</p>
  
  <blockquote>
    <p>ValueError("Unknown label type: %s" % repr(ys))
    ValueError: Unknown label type: (array([ 0.3,  3. ]),)</p>
  </blockquote>
  
  <p>How can I get around the issue without using a different naive bayes module than the one provided by Sklearn?</p>