<p>Great to hear that it's faster for k=1, too.</p>
<p>It's funny, this is kind of things coming full circle... a very long time ago, the NeighborSearch code (or AllkNN as the class was called) used to use <code>std::pair<></code> to represent candidates:</p>
<p><a href="https://github.com/mlpack/mlpack/blob/43ac2c8a0f165aecb91ef5a5e8f9e0e7e0b3bb55/fastlib/trunk/mlpack/allknn/allknn.h#L375">https://github.com/mlpack/mlpack/blob/43ac2c8a0f165aecb91ef5a5e8f9e0e7e0b3bb55/fastlib/trunk/mlpack/allknn/allknn.h#L375</a><br>
(it's crazy how different the code was then... I forget how far things have come. It's fun to browse around that repository and contrast with now)</p>
<p>But it used <code>std::vector<std::pair<>></code> and then used <code>std::sort()</code> to sort them and remove the last element, instead of the much more reasonable priority queue. When I replaced that (back in 2011 sometime) with individual vectors for the neighbors and distances, I achieved an order-of-magnitude speedup or more, especially for large k. Now we are back to using <code>std::pair<></code> (or similar), but this time with the right data structure---a heap. :)</p>
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