[mlpack] [mlpack/mlpack] adds GammaDistribution::Train(observations, probabilities) (#834)

[Ryan Curtin]

rcurtin commented on this pull request.



> +  for(size_t i = 0; i < N; i++)
+    probabilities(i) = prob(generator);
+
+  // fit results with probabilities and data
+  GammaDistribution gDist;
+  gDist.Train(rdata, probabilities);
+
+  // fit results with only data
+  GammaDistribution gDist2;
+  gDist2.Train(rdata);
+
+  BOOST_REQUIRE_CLOSE(gDist2.Alpha(0), gDist.Alpha(0), 10);
+  BOOST_REQUIRE_CLOSE(gDist2.Beta(0), gDist.Beta(0), 10);
+
+  BOOST_REQUIRE_CLOSE(alphaReal, gDist.Alpha(0), 10);
+  BOOST_REQUIRE_CLOSE(betaReal, gDist.Beta(0), 10);

Hm, ok, a larger tolerance like 5% (or even 10% if need be) is okay for the difference between alphaReal and gDist.Alpha(0), but the tolerance between gDist and gDist2 should be 1e-5.  The gDist/gDist2 tolerance is really the one I'm much more concerned with.

One way you can test a tolerance is by adding `math::RandomSeed(std::time(NULL))` (although you are using different RNGs so you'll have to set them accordingly) and then running the test over and over again to see how often it fails.

-- 
You are receiving this because you commented.
Reply to this email directly or view it on GitHub:
https://github.com/mlpack/mlpack/pull/834
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://knife.lugatgt.org/pipermail/mlpack/attachments/20161222/522bb368/attachment-0001.html>