diff --git a/src/mlpack/tests/main_tests/gmm_generate_test.cpp b/src/mlpack/tests/main_tests/gmm_generate_test.cpp
index 1d725a28e6..494b99097d 100644
--- a/src/mlpack/tests/main_tests/gmm_generate_test.cpp
+++ b/src/mlpack/tests/main_tests/gmm_generate_test.cpp
@@ -45,8 +45,8 @@ BOOST_AUTO_TEST_CASE(GmmGenerateSamplesTest)
 {
   arma::mat inputData(5, 10, arma::fill::randu);
 
-  GMM gmm(1, 2);
-  gmm.Train(inputData, 2);
+  GMM gmm(1, 5);
+  gmm.Train(inputData, 5);
 
   SetInputParam("input_model", &gmm);
 
@@ -61,8 +61,8 @@ BOOST_AUTO_TEST_CASE(GmmGenerateSamples)
 {
   arma::mat inputData(5, 10, arma::fill::randu);
 
-  GMM gmm(1, 2);
-  gmm.Train(inputData, 2);
+  GMM gmm(1, 5);
+  gmm.Train(inputData, 5);
 
   SetInputParam("input_model", &gmm);
 
@@ -76,8 +76,8 @@ BOOST_AUTO_TEST_CASE(GmmGenerateDimensionality)
 {
   arma::mat inputData(5, 10, arma::fill::randu);
 
-  GMM gmm(1, 2);
-  gmm.Train(inputData, 2);
+  GMM gmm(1, 5);
+  gmm.Train(inputData, 5);
   SetInputParam("input_model", &gmm);
   SetInputParam("samples", (int) 10);
 
diff --git a/src/mlpack/tests/main_tests/gmm_probability_test.cpp b/src/mlpack/tests/main_tests/gmm_probability_test.cpp
index f945ea134b..17d5a8f983 100644
--- a/src/mlpack/tests/main_tests/gmm_probability_test.cpp
+++ b/src/mlpack/tests/main_tests/gmm_probability_test.cpp
@@ -54,8 +54,8 @@ BOOST_AUTO_TEST_CASE(GmmProbabilityDimensionality)
 {
   arma::mat inputData(5, 10, arma::fill::randu);
 
-  GMM gmm(1, 2);
-  gmm.Train(std::move(inputData), 2);
+  GMM gmm(1, 5);
+  gmm.Train(std::move(inputData), 5);
 
   arma::mat inputPoints(1, 8, arma::fill::randu);
 
diff --git a/src/mlpack/tests/main_tests/gmm_train_test.cpp b/src/mlpack/tests/main_tests/gmm_train_test.cpp
index 85074fdc62..2a9d1672a4 100644
--- a/src/mlpack/tests/main_tests/gmm_train_test.cpp
+++ b/src/mlpack/tests/main_tests/gmm_train_test.cpp
@@ -47,6 +47,7 @@ void ResetGmmTrainSetting()
   CLI::RestoreSettings(testName);
 }
 
+
 BOOST_FIXTURE_TEST_SUITE(GmmTrainMainTest, GmmTrainTestFixture);
 
 // To check if the gaussian is positive or not.
@@ -175,17 +176,18 @@ BOOST_AUTO_TEST_CASE(GmmTrainNoisetest)
   SetInputParam("gaussians", (int) 2);
   SetInputParam("noise", (double) 0.0);
 
+  mlpack::math::FixedRandomSeed();
   mlpackMain();
 
   GMM* gmm = CLI::GetParam<GMM*>("output_model");
 
-  CLI::GetSingleton().Parameters()["input"].wasPassed = false;
-  CLI::GetSingleton().Parameters()["gaussians"].wasPassed = false;
-  CLI::GetSingleton().Parameters()["noise"].wasPassed = false;
+  ResetGmmTrainSetting();
 
   SetInputParam("input", std::move(inputData));
   SetInputParam("gaussians", (int) 2);
-  SetInputParam("noise", (double) 1.5);
+  SetInputParam("noise", (double) 100.0);
+
+  mlpack::math::FixedRandomSeed();
   mlpackMain();
 
   GMM* gmm1 = CLI::GetParam<GMM*>("output_model");
@@ -193,8 +195,10 @@ BOOST_AUTO_TEST_CASE(GmmTrainNoisetest)
   arma::uvec sortedIndices = sort_index(gmm->Weights());
 
   for (size_t k = 0; k < sortedIndices.n_elem; k++)
-    CheckMatricesNotEqual(gmm->Component(sortedIndices[k]).Covariance(),
-                            gmm1->Component(sortedIndices[k]).Covariance());
+    BOOST_REQUIRE(arma::norm(gmm->Component(sortedIndices[k]).Mean() -
+                      gmm1->Component(sortedIndices[k]).Mean()) > 1e-50 ||
+                  arma::norm(gmm->Component(sortedIndices[k]).Covariance() -
+                      gmm1->Component(sortedIndices[k]).Covariance()) > 1e-50);
 }
 
 // Ensure that Percentage affects the final result when refined_start is true.
@@ -205,22 +209,23 @@ BOOST_AUTO_TEST_CASE(GmmTrainPercentageTest)
   SetInputParam("input", inputData);
   SetInputParam("gaussians", (int) 2);
   SetInputParam("refined_start", true);
-  SetInputParam("percentage", (double) 0.22);
+  SetInputParam("percentage", (double) 0.01);
+  SetInputParam("samplings", (int) 200);
 
+  mlpack::math::FixedRandomSeed();
   mlpackMain();
 
   GMM* gmm = CLI::GetParam<GMM*>("output_model");
 
-  CLI::GetSingleton().Parameters()["input"].wasPassed = false;
-  CLI::GetSingleton().Parameters()["gaussians"].wasPassed = false;
-  CLI::GetSingleton().Parameters()["refined_start"].wasPassed = false;
-  CLI::GetSingleton().Parameters()["percentage"].wasPassed = false;
+  ResetGmmTrainSetting();
 
   SetInputParam("input", std::move(inputData));
   SetInputParam("gaussians", (int) 2);
   SetInputParam("refined_start", true);
-  SetInputParam("percentage", (double) 0.82);
+  SetInputParam("percentage", (double) 0.99);
+  SetInputParam("samplings", (int) 200);
 
+  mlpack::math::FixedRandomSeed();
   mlpackMain();
 
   GMM* gmm1 = CLI::GetParam<GMM*>("output_model");
@@ -228,8 +233,10 @@ BOOST_AUTO_TEST_CASE(GmmTrainPercentageTest)
   arma::uvec sortedIndices = sort_index(gmm->Weights());
 
   for (size_t k = 0; k < sortedIndices.n_elem; k++)
-    CheckMatricesNotEqual(gmm->Component(sortedIndices[k]).Covariance(),
-                            gmm1->Component(sortedIndices[k]).Covariance());
+    BOOST_REQUIRE(arma::norm(gmm->Component(sortedIndices[k]).Mean() -
+                      gmm1->Component(sortedIndices[k]).Mean()) > 1e-50 ||
+                  arma::norm(gmm->Component(sortedIndices[k]).Covariance() -
+                      gmm1->Component(sortedIndices[k]).Covariance()) > 1e-50);
 }
 
 // Ensure that Sampling affects the final result when refined_start is true.
@@ -240,25 +247,23 @@ BOOST_AUTO_TEST_CASE(GmmTrainSamplingsTest)
   SetInputParam("input", inputData);
   SetInputParam("gaussians", (int) 2);
   SetInputParam("refined_start", true);
-  SetInputParam("percentage", (double) 0.5);
-  SetInputParam("samplings", (int) 100);
+  SetInputParam("percentage", (double) 0.950);
+  SetInputParam("samplings", (int) 10);
 
+  mlpack::math::FixedRandomSeed();
   mlpackMain();
 
   GMM* gmm = CLI::GetParam<GMM*>("output_model");
 
-  CLI::GetSingleton().Parameters()["input"].wasPassed = false;
-  CLI::GetSingleton().Parameters()["gaussians"].wasPassed = false;
-  CLI::GetSingleton().Parameters()["refined_start"].wasPassed = false;
-  CLI::GetSingleton().Parameters()["percentage"].wasPassed = false;
-  CLI::GetSingleton().Parameters()["samplings"].wasPassed = false;
+  ResetGmmTrainSetting();
 
   SetInputParam("input", std::move(inputData));
   SetInputParam("gaussians", (int) 2);
   SetInputParam("refined_start", true);
-  SetInputParam("percentage", (double) 0.5);
-  SetInputParam("samplings", (int) 500);
+  SetInputParam("percentage", (double) 0.950);
+  SetInputParam("samplings", (int) 1000);
 
+  mlpack::math::FixedRandomSeed();
   mlpackMain();
 
   GMM* gmm1 = CLI::GetParam<GMM*>("output_model");
@@ -266,9 +271,10 @@ BOOST_AUTO_TEST_CASE(GmmTrainSamplingsTest)
   arma::uvec sortedIndices = sort_index(gmm->Weights());
 
   for (size_t k = 0; k < sortedIndices.n_elem; k++)
-    CheckMatricesNotEqual(gmm->Component(sortedIndices[k]).Covariance(),
-                            gmm1->Component(sortedIndices[k]).Covariance());
-
+    BOOST_REQUIRE(arma::norm(gmm->Component(sortedIndices[k]).Mean() -
+                      gmm1->Component(sortedIndices[k]).Mean()) > 1e-50 ||
+                  arma::norm(gmm->Component(sortedIndices[k]).Covariance() -
+                      gmm1->Component(sortedIndices[k]).Covariance()) > 1e-50);
 }
 
 // Ensure that tolerance affects the final result.
@@ -280,20 +286,20 @@ BOOST_AUTO_TEST_CASE(GmmTrainToleranceTest)
 
   SetInputParam("input", inputData);
   SetInputParam("gaussians", (int) 2);
-  SetInputParam("tolerance", (double) 1e-10);
+  SetInputParam("tolerance", (double) 1e-8);
 
+  mlpack::math::FixedRandomSeed();
   mlpackMain();
 
   GMM* gmm = CLI::GetParam<GMM*>("output_model");
 
-  CLI::GetSingleton().Parameters()["input"].wasPassed = false;
-  CLI::GetSingleton().Parameters()["gaussians"].wasPassed = false;
-  CLI::GetSingleton().Parameters()["tolerance"].wasPassed = false;
+  ResetGmmTrainSetting();
 
   SetInputParam("input", std::move(inputData));
   SetInputParam("gaussians", (int) 2);
-  SetInputParam("tolerance", (double) 1e-30);
+  SetInputParam("tolerance", (double) 10);
 
+  mlpack::math::FixedRandomSeed();
   mlpackMain();
 
   GMM* gmm1 = CLI::GetParam<GMM*>("output_model");
@@ -301,8 +307,10 @@ BOOST_AUTO_TEST_CASE(GmmTrainToleranceTest)
   arma::uvec sortedIndices = sort_index(gmm->Weights());
 
   for (size_t k = 0; k < sortedIndices.n_elem; k++)
-    CheckMatricesNotEqual(gmm->Component(sortedIndices[k]).Covariance(),
-                            gmm1->Component(sortedIndices[k]).Covariance());
+    BOOST_REQUIRE(arma::norm(gmm->Component(sortedIndices[k]).Mean() -
+                      gmm1->Component(sortedIndices[k]).Mean()) > 1e-50 ||
+                  arma::norm(gmm->Component(sortedIndices[k]).Covariance() -
+                      gmm1->Component(sortedIndices[k]).Covariance()) > 1e-50);
 }
 
 // Ensure that saved model can be used again.