Reduce dataset sizes and number of iterations to accelerate tests.

src/mlpack/tests/kmeans_test.cpp

@@ -608,7 +608,7 @@ BOOST_AUTO_TEST_CASE(DTNNTest)
 
   for (size_t t = 0; t < trials; ++t)
   {
-    arma::mat dataset(10, 1000);
+    arma::mat dataset(10, 300);
     dataset.randu();
 
     const size_t k = 5 * (t + 1);
@@ -640,7 +640,7 @@ BOOST_AUTO_TEST_CASE(DTNNCoverTreeTest)
 
   for (size_t t = 0; t < trials; ++t)
   {
-    arma::mat dataset(10, 1000);
+    arma::mat dataset(10, 300);
     dataset.randu();
 
     const size_t k = 5;

src/mlpack/tests/minibatch_sgd_test.cpp

@@ -121,7 +121,7 @@ BOOST_AUTO_TEST_CASE(LogisticRegressionTest)
   // Now run mini-batch SGD with a couple of batch sizes.
   for (size_t batchSize = 5; batchSize < 50; batchSize += 5)
   {
-    MiniBatchSGD mbsgd(batchSize);
+    MiniBatchSGD mbsgd(batchSize, 0.01, 10000, 1e-3);
     LogisticRegression<> lr(shuffledData, shuffledResponses, mbsgd, 0.5);
 
     // Ensure that the error is close to zero.

src/mlpack/tests/ub_tree_test.cpp

@@ -251,7 +251,7 @@ void CheckDistance(TreeType& tree, TreeType* node = NULL)
 BOOST_AUTO_TEST_CASE(UBTreeDistanceTest)
 {
   typedef UBTree<EuclideanDistance, EmptyStatistic, arma::mat> TreeType;
-  arma::mat dataset(8, 1000);
+  arma::mat dataset(8, 200);
 
   dataset.randu();