title: confused with the output of sklearn.neighbors.NearestNeighbors
body: <p>Here is the code.</p>
  
  <pre><code>from sklearn.neighbors import NearestNeighbors
  import numpy as np
  X = np.array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]])
  nbrs = NearestNeighbors(n_neighbors=2, algorithm='ball_tree').fit(X)
  distances, indices = nbrs.kneighbors(X)
  
  
  &gt;indices
  
  &gt;array([[0, 1],[1, 0],[2, 1],[3, 4],[4, 3],[5, 4]])
  
  &gt;distances
  
  &gt;array([[0.        , 1.        ],[0.        , 1.        ],[0.        , 1.41421356], [0.        , 1.        ],[0.        , 1.        ],[0.        , 1.41421356]])
  </code></pre>
  
  <p>I don't really understand the shape of 'indices' and 'distances'. How do I understand what these numbers mean?</p>