<p>In <a href="https://github.com/mlpack/mlpack/pull/388#discussion_r23584112">src/mlpack/tests/mean_shift_test.cpp</a>:</p>
<pre style='color:#555'>> + BOOST_REQUIRE_NE(firstClass, secondClass);
> +
> + for (size_t i = 13; i < 20; i++)
> + BOOST_REQUIRE_EQUAL(assignments(i), secondClass);
> +
> + size_t thirdClass = assignments(20);
> +
> + // To ensure that this is the third class which we haven't seen yet.
> + BOOST_REQUIRE_NE(firstClass, thirdClass);
> + BOOST_REQUIRE_NE(secondClass, thirdClass);
> +
> + for (size_t i = 20; i < 30; i++)
> + BOOST_REQUIRE_EQUAL(assignments(i), thirdClass);
> +
> +}
> +
</pre>
<p>Once we merge this I will probably add at least one more test where I generate observations from a mixture of Gaussians (that are sufficiently far apart) and ensure that the mean shift algorithm will properly label each point. You can do this now if you like, but I wanted to let you know that I'm planning to do that. More tests, in general, is a good thing. It may be worth adding some simple tests like "if I set the duplicate threshold to 0, do I get dataset.n_cols clusters?"; this is helpful to people who might be modifying the code later on and want to make sure it still functions the same way.</p>
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