<p>In <a href="https://github.com/mlpack/mlpack/pull/746#discussion_r75233467">src/mlpack/core/tree/cellbound_impl.hpp</a>:</p>
<pre style='color:#555'>> + ElemType lower, higher;
> +
> + for (size_t i = 0; i < numBounds; i++)
> + {
> + ElemType sum = 0;
> +
> + for (size_t d = 0; d < dim; d++)
> + {
> + lower = loBound(d, i) - point[d];
> + higher = point[d] - hiBound(d, i);
> +
> + // Since only one of 'lower' or 'higher' is negative, if we add each's
> + // absolute value to itself and then sum those two, our result is the
> + // nonnegative half of the equation times two; then we raise to power Power.
> + sum += pow((lower + fabs(lower)) + (higher + fabs(higher)),
> + (ElemType) MetricType::Power);
</pre>
<p>You can save a little bit of computation here if you terminate early:</p>
<pre><code>if (sum >= minSum)
continue;
</code></pre>
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