[mlpack] 48/149: A test for the DTNN k-means algorithm.

[Barak A. Pearlmutter]

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commit 363349e21bfb0c3367ae6f5a20d18fda9e32a932
Author: rcurtin <rcurtin at 9d5b8971-822b-0410-80eb-d18c1038ef23>
Date:   Mon Oct 13 21:07:28 2014 +0000

    A test for the DTNN k-means algorithm.
    
    
    git-svn-id: http://svn.cc.gatech.edu/fastlab/mlpack/trunk@17256 9d5b8971-822b-0410-80eb-d18c1038ef23
---
 src/mlpack/tests/kmeans_test.cpp | 33 +++++++++++++++++++++++++++++++++
 1 file changed, 33 insertions(+)

diff --git a/src/mlpack/tests/kmeans_test.cpp b/src/mlpack/tests/kmeans_test.cpp
index 178bdb5..0b22195 100644
--- a/src/mlpack/tests/kmeans_test.cpp
+++ b/src/mlpack/tests/kmeans_test.cpp
@@ -10,6 +10,7 @@
 #include <mlpack/methods/kmeans/elkan_kmeans.hpp>
 #include <mlpack/methods/kmeans/hamerly_kmeans.hpp>
 #include <mlpack/methods/kmeans/pelleg_moore_kmeans.hpp>
+#include <mlpack/methods/kmeans/dtnn_kmeans.hpp>
 
 #include <boost/test/unit_test.hpp>
 #include "old_boost_test_definitions.hpp"
@@ -590,4 +591,36 @@ BOOST_AUTO_TEST_CASE(PellegMooreTest)
   }
 }
 
+BOOST_AUTO_TEST_CASE(DTNNTest)
+{
+  const size_t trials = 5;
+
+  for (size_t t = 0; t < trials; ++t)
+  {
+    arma::mat dataset(10, 1000);
+    dataset.randu();
+
+    const size_t k = 5 * (t + 1);
+    arma::mat centroids(10, k);
+    centroids.randu();
+
+    arma::mat naiveCentroids(centroids);
+    KMeans<> km;
+    arma::Col<size_t> assignments;
+    km.Cluster(dataset, k, assignments, naiveCentroids, false, true);
+
+    KMeans<metric::EuclideanDistance, RandomPartition, MaxVarianceNewCluster,
+        DefaultDTNNKMeans> dtnn;
+    arma::Col<size_t> dtnnAssignments;
+    arma::mat dtnnCentroids(centroids);
+    dtnn.Cluster(dataset, k, dtnnAssignments, dtnnCentroids, false, true);
+
+    for (size_t i = 0; i < dataset.n_cols; ++i)
+      BOOST_REQUIRE_EQUAL(assignments[i], dtnnAssignments[i]);
+
+    for (size_t i = 0; i < centroids.n_cols; ++i)
+      BOOST_REQUIRE_CLOSE(naiveCentroids[i], dtnnCentroids[i], 1e-5);
+  }
+}
+
 BOOST_AUTO_TEST_SUITE_END();

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