<p>In <a href="https://github.com/mlpack/mlpack/pull/726#discussion_r73701401">src/mlpack/core/tree/binary_space_tree/rp_tree_mean_split_impl.hpp</a>:</p>
<pre style='color:#555'>> + ElemType length = metric::EuclideanDistance::Evaluate(origin, direction);
> +
> + if (length > 0)
> + direction /= length;
> + else
> + {
> + // If the vector is equal to 0, choose an arbitrary dimension.
> + size_t k = math::RandInt(direction.n_rows);
> +
> + direction[k] = 1.0;
> +
> + length = metric::EuclideanDistance::Evaluate(origin, direction);
> +
> + direction[k] /= length;
> + }
> +}
</pre>
<p>I think this also can be replaced with the shorter function idea I sketched in another comment. Another thought is, since you are using it twice, maybe mark the function static in <code>RPTreeMaxSplit</code> and then call it from <code>RPTreeMeanSplit</code> instead of implementing it again here. I am not sure this is a great function to add to the core mlpack code, because of its odd behavior when a vector of length 0 is selected. Is that behavior the best thing to do here, or maybe is it better to simply draw a random vector again?</p>
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