diff --git a/src/mlpack/methods/kmeans/kmeans_impl.hpp b/src/mlpack/methods/kmeans/kmeans_impl.hpp
index 7e52464ced..ac4f4cc748 100644
--- a/src/mlpack/methods/kmeans/kmeans_impl.hpp
+++ b/src/mlpack/methods/kmeans/kmeans_impl.hpp
@@ -164,7 +164,6 @@ Cluster(const MatType& data,
   if (initialGuess)
   {
     util::CheckSameSizes(centroids, clusters, "KMeans::Cluster()", "clusters");
-
     util::CheckSameDimensionality(data, centroids, "KMeans::Cluster()");
   }
 
@@ -284,7 +283,7 @@ Cluster(const MatType& data,
   // Now, the initial assignments.  First determine if they are necessary.
   if (initialAssignmentGuess)
   {
-    util::CheckSameSizes(data, assignments, "KMeans::Cluster()","assignments");
+    util::CheckSameSizes(data, assignments, "KMeans::Cluster()", "assignments");
 
     // Calculate initial centroids.
     arma::Row<size_t> counts;
diff --git a/src/mlpack/methods/linear_regression/linear_regression.cpp b/src/mlpack/methods/linear_regression/linear_regression.cpp
index 744e184f18..17f9e72a76 100644
--- a/src/mlpack/methods/linear_regression/linear_regression.cpp
+++ b/src/mlpack/methods/linear_regression/linear_regression.cpp
@@ -100,7 +100,7 @@ void LinearRegression::Predict(const arma::mat& points,
   {
     // We want to be sure we have the correct number of dimensions in the
     // dataset.
-    util::CheckSameDimensionality(points, (size_t) (parameters.n_rows-1), "LinearRegression::Predict()", "points");
+    util::CheckSameDimensionality(points, (size_t) (parameters.n_rows - 1), "LinearRegression::Predict()", "points");
     // Get the predictions, but this ignores the intercept value
     // (parameters[0]).
     predictions = arma::trans(parameters.subvec(1, parameters.n_elem - 1))