<p>In <a href="https://github.com/mlpack/mlpack/pull/684#discussion_r66666544">src/mlpack/tests/test_tools.hpp</a>:</p>
<pre style='color:#555'>> @@ -35,4 +34,9 @@
>
> #endif
>
> +// Require the approximation L to be within a relative error of E respect to the
> +// actual value R.
> +#define REQUIRE_RELATIVE_ERR( L, R, E ) \
> + BOOST_REQUIRE_LE( abs((R) - (L)), (E) * (R))
</pre>
<p>It's up to you (or, at least, I don't have a strong opinion). The only issue with adding <code>REQUIRE_RELATIVE_ERR</code> is that it should be clearly documented, because another developer might expect something a little different out of a relative error condition. Personally, I might consider using <code>BOOST_REQUIRE_CLOSE</code> with tolerance epsilon for KNN and with tolerance epsilon(1 + epsilon) for KFN (I think I did those calculations right) in order to avoid adding a new macro, but like I said, either way is fine, as long as the new macro is well-documented.</p>
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