diff --git a/src/mlpack/core/tree/rectangle_tree/discrete_hilbert_value.hpp b/src/mlpack/core/tree/rectangle_tree/discrete_hilbert_value.hpp
index 405188a4f6..32bb94ece9 100644
--- a/src/mlpack/core/tree/rectangle_tree/discrete_hilbert_value.hpp
+++ b/src/mlpack/core/tree/rectangle_tree/discrete_hilbert_value.hpp
@@ -182,6 +182,14 @@ class DiscreteHilbertValue
    */
   DiscreteHilbertValue& operator=(const DiscreteHilbertValue& val);
 
+   /**
+   * Move the local Hilbert object.
+   *
+   * @param val The DiscreteHilbertValue object from which the dataset
+   *    will be copied.
+   */
+  DiscreteHilbertValue& operator=(DiscreteHilbertValue&& val);
+
   /**
    * Nullify the localHilbertValues pointer in order to prevent an invalid free.
    */
diff --git a/src/mlpack/core/tree/rectangle_tree/discrete_hilbert_value_impl.hpp b/src/mlpack/core/tree/rectangle_tree/discrete_hilbert_value_impl.hpp
index c4baa38a90..48ad8557f7 100644
--- a/src/mlpack/core/tree/rectangle_tree/discrete_hilbert_value_impl.hpp
+++ b/src/mlpack/core/tree/rectangle_tree/discrete_hilbert_value_impl.hpp
@@ -450,6 +450,27 @@ operator=(const DiscreteHilbertValue& val)
   return *this;
 }
 
+template<typename TreeElemType>
+DiscreteHilbertValue<TreeElemType>& DiscreteHilbertValue<TreeElemType>::
+operator=(DiscreteHilbertValue&& other)
+{
+  if (this != &other)
+  {
+    localHilbertValues = other.localHilbertValues;
+    ownsLocalHilbertValues = other.ownsLocalHilbertValues;
+    numValues = other.numValues;
+    valueToInsert = other.valueToInsert;
+    ownsValueToInsert = other.ownsValueToInsert;
+
+    other.localHilbertValues = nullptr;
+    other.ownsLocalHilbertValues = false;
+    other.numValues = 0;
+    other.valueToInsert = nullptr;
+    other.ownsValueToInsert = false;
+  }
+  return *this;
+}
+
 template<typename TreeElemType>
 void DiscreteHilbertValue<TreeElemType>::NullifyData()
 {
diff --git a/src/mlpack/methods/amf/termination_policies/simple_residue_termination.hpp b/src/mlpack/methods/amf/termination_policies/simple_residue_termination.hpp
index 970b24289f..81893f4fa3 100644
--- a/src/mlpack/methods/amf/termination_policies/simple_residue_termination.hpp
+++ b/src/mlpack/methods/amf/termination_policies/simple_residue_termination.hpp
@@ -41,7 +41,15 @@ class SimpleResidueTermination
    */
   SimpleResidueTermination(const double minResidue = 1e-5,
                            const size_t maxIterations = 10000)
-      : minResidue(minResidue), maxIterations(maxIterations) { }
+      : minResidue(minResidue), 
+        maxIterations(maxIterations), 
+        residue(0.0), 
+        iteration(0), 
+        nm(0), 
+        normOld(0) 
+  { 
+    // Nothing to do here.
+  }
 
   /**
    * Initializes the termination policy before stating the factorization.
diff --git a/src/mlpack/methods/amf/update_rules/svd_complete_incremental_learning.hpp b/src/mlpack/methods/amf/update_rules/svd_complete_incremental_learning.hpp
index 4ab1c0d610..37b7ab8c0a 100644
--- a/src/mlpack/methods/amf/update_rules/svd_complete_incremental_learning.hpp
+++ b/src/mlpack/methods/amf/update_rules/svd_complete_incremental_learning.hpp
@@ -56,7 +56,7 @@ class SVDCompleteIncrementalLearning
   SVDCompleteIncrementalLearning(double u = 0.0001,
                                  double kw = 0,
                                  double kh = 0)
-            : u(u), kw(kw), kh(kh)
+            : u(u), kw(kw), kh(kh), currentUserIndex(0), currentItemIndex(0)
   {
     // Nothing to do.
   }
@@ -172,7 +172,7 @@ class SVDCompleteIncrementalLearning<arma::sp_mat>
   SVDCompleteIncrementalLearning(double u = 0.01,
                                  double kw = 0,
                                  double kh = 0)
-            : u(u), kw(kw), kh(kh), it(NULL)
+            : u(u), kw(kw), kh(kh), it(NULL), m(0), n(0), isStart(false)
     {}
 
   ~SVDCompleteIncrementalLearning()
diff --git a/src/mlpack/methods/amf/update_rules/svd_incomplete_incremental_learning.hpp b/src/mlpack/methods/amf/update_rules/svd_incomplete_incremental_learning.hpp
index 0082824129..9880ea2945 100644
--- a/src/mlpack/methods/amf/update_rules/svd_incomplete_incremental_learning.hpp
+++ b/src/mlpack/methods/amf/update_rules/svd_incomplete_incremental_learning.hpp
@@ -53,7 +53,7 @@ class SVDIncompleteIncrementalLearning
   SVDIncompleteIncrementalLearning(double u = 0.001,
                                    double kw = 0,
                                    double kh = 0)
-          : u(u), kw(kw), kh(kh)
+          : u(u), kw(kw), kh(kh), currentUserIndex(0)
   {
     // Nothing to do.
   }
diff --git a/src/mlpack/methods/fastmks/fastmks.hpp b/src/mlpack/methods/fastmks/fastmks.hpp
index 93d234d541..ea2057b0b9 100644
--- a/src/mlpack/methods/fastmks/fastmks.hpp
+++ b/src/mlpack/methods/fastmks/fastmks.hpp
@@ -163,6 +163,11 @@ class FastMKS
    */
   FastMKS& operator=(const FastMKS& other);
 
+  /**
+   * Move assignment operator.
+   */
+  FastMKS& operator=(FastMKS&& other);
+
   //! Destructor for the FastMKS object.
   ~FastMKS();
 
diff --git a/src/mlpack/methods/fastmks/fastmks_impl.hpp b/src/mlpack/methods/fastmks/fastmks_impl.hpp
index 660617fdb0..3b2d12eaae 100644
--- a/src/mlpack/methods/fastmks/fastmks_impl.hpp
+++ b/src/mlpack/methods/fastmks/fastmks_impl.hpp
@@ -250,6 +250,35 @@ FastMKS<KernelType, MatType, TreeType>::operator=(const FastMKS& other)
   naive = other.naive;
 }
 
+template<typename KernelType,
+         typename MatType,
+         template<typename TreeMetricType,
+                  typename TreeStatType,
+                  typename TreeMatType> class TreeType>
+FastMKS<KernelType, MatType, TreeType>&
+FastMKS<KernelType, MatType, TreeType>::operator=(FastMKS&& other)
+{
+  if (this != &other)
+  {
+    referenceSet = other.referenceSet;
+    referenceTree = other.referenceTree;
+    treeOwner = other.treeOwner;
+    setOwner = other.setOwner;
+    singleMode = other.singleMode;
+    naive = other.naive;
+    metric = std::move(other.metric);
+
+    // Clear information from the other.
+    other.referenceSet = nullptr;
+    other.referenceTree = nullptr;
+    other.treeOwner = false;
+    other.setOwner = false;
+    other.singleMode = false;
+    other.naive = false;
+  }
+  return *this;
+}
+
 template<typename KernelType,
          typename MatType,
          template<typename TreeMetricType,
diff --git a/src/mlpack/methods/fastmks/fastmks_model.cpp b/src/mlpack/methods/fastmks/fastmks_model.cpp
index 2fcda8e831..ae557d2358 100644
--- a/src/mlpack/methods/fastmks/fastmks_model.cpp
+++ b/src/mlpack/methods/fastmks/fastmks_model.cpp
@@ -71,40 +71,68 @@ FastMKSModel::FastMKSModel(FastMKSModel&& other) :
 
 FastMKSModel& FastMKSModel::operator=(const FastMKSModel& other)
 {
-  // Clear memory.
-  delete linear;
-  delete polynomial;
-  delete cosine;
-  delete gaussian;
-  delete epan;
-  delete triangular;
-  delete hyptan;
+  if (this != &other)
+  {
+    // Clear memory.
+    delete linear;
+    delete polynomial;
+    delete cosine;
+    delete gaussian;
+    delete epan;
+    delete triangular;
+    delete hyptan;
 
-  // Set pointers to null.
-  linear = NULL;
-  polynomial = NULL;
-  cosine = NULL;
-  gaussian = NULL;
-  epan = NULL;
-  triangular = NULL;
-  hyptan = NULL;
+    // Set pointers to null.
+    linear = NULL;
+    polynomial = NULL;
+    cosine = NULL;
+    gaussian = NULL;
+    epan = NULL;
+    triangular = NULL;
+    hyptan = NULL;
 
-  kernelType = other.kernelType;
-  if (other.linear)
-    linear = new FastMKS<LinearKernel>(*other.linear);
-  if (other.polynomial)
-    polynomial = new FastMKS<PolynomialKernel>(*other.polynomial);
-  if (other.cosine)
-    cosine = new FastMKS<CosineDistance>(*other.cosine);
-  if (other.gaussian)
-    gaussian = new FastMKS<GaussianKernel>(*other.gaussian);
-  if (other.epan)
-    epan = new FastMKS<EpanechnikovKernel>(*other.epan);
-  if (other.triangular)
-    triangular = new FastMKS<TriangularKernel>(*other.triangular);
-  if (other.hyptan)
-    hyptan = new FastMKS<HyperbolicTangentKernel>(*other.hyptan);
+    kernelType = other.kernelType;
+    if (other.linear)
+      linear = new FastMKS<LinearKernel>(*other.linear);
+    if (other.polynomial)
+      polynomial = new FastMKS<PolynomialKernel>(*other.polynomial);
+    if (other.cosine)
+      cosine = new FastMKS<CosineDistance>(*other.cosine);
+    if (other.gaussian)
+      gaussian = new FastMKS<GaussianKernel>(*other.gaussian);
+    if (other.epan)
+      epan = new FastMKS<EpanechnikovKernel>(*other.epan);
+    if (other.triangular)
+      triangular = new FastMKS<TriangularKernel>(*other.triangular);
+    if (other.hyptan)
+      hyptan = new FastMKS<HyperbolicTangentKernel>(*other.hyptan);
+  }
+  return *this;
+}
 
+FastMKSModel& FastMKSModel::operator=(FastMKSModel&& other)
+{
+  if (this != &other)
+  {
+    kernelType = other.kernelType;
+    linear = other.linear;
+    polynomial = other.polynomial;
+    cosine = other.cosine;
+    gaussian = other.gaussian;
+    epan = other.epan;
+    triangular = other.triangular;
+    hyptan = other.hyptan;
+
+    // Clear other object.
+    other.kernelType = KernelTypes::LINEAR_KERNEL;
+    other.linear = nullptr;
+    other.polynomial = nullptr;
+    other.cosine = nullptr;
+    other.gaussian = nullptr;
+    other.epan = nullptr;
+    other.triangular = nullptr;
+    other.hyptan = nullptr;
+  }
   return *this;
 }
 
diff --git a/src/mlpack/methods/fastmks/fastmks_model.hpp b/src/mlpack/methods/fastmks/fastmks_model.hpp
index e84eee0c28..0b7568c641 100644
--- a/src/mlpack/methods/fastmks/fastmks_model.hpp
+++ b/src/mlpack/methods/fastmks/fastmks_model.hpp
@@ -60,6 +60,9 @@ class FastMKSModel
   //! Copy assignment operator.
   FastMKSModel& operator=(const FastMKSModel& other);
 
+  //! Move assignment operator.
+  FastMKSModel& operator=(FastMKSModel&& other);
+
   /**
    * Clean memory.
    */
diff --git a/src/mlpack/methods/hmm/hmm_model.hpp b/src/mlpack/methods/hmm/hmm_model.hpp
index 41a7fd406b..0a2bce384b 100644
--- a/src/mlpack/methods/hmm/hmm_model.hpp
+++ b/src/mlpack/methods/hmm/hmm_model.hpp
@@ -129,6 +129,20 @@ class HMMModel
     return *this;
   }
 
+  //! Move assignment operator.
+  HMMModel& operator=(HMMModel&& other)
+  {
+    if (this != &other)
+    {
+      type = other.type;
+      discreteHMM = other.discreteHMM;
+      gaussianHMM = other.gaussianHMM;
+      gmmHMM = other.gmmHMM;
+      diagGMMHMM = other.diagGMMHMM;
+    }
+    return *this;
+  }
+
   //! Clean memory.
   ~HMMModel()
   {
diff --git a/src/mlpack/methods/range_search/range_search.hpp b/src/mlpack/methods/range_search/range_search.hpp
index 06575005ac..98de888a69 100644
--- a/src/mlpack/methods/range_search/range_search.hpp
+++ b/src/mlpack/methods/range_search/range_search.hpp
@@ -122,12 +122,18 @@ class RangeSearch
   RangeSearch(RangeSearch&& other);
 
   /**
-   * Copy the given RangeSearch model.
-   * Use std::move to pass in the model if the old copy is no longer needed.
-   *
+   * Deep copy the given RangeSearch model.
+   * 
    * @param other RangeSearch model to copy.
    */
-  RangeSearch& operator=(RangeSearch other);
+  RangeSearch& operator=(const RangeSearch& other);
+
+  /**
+   * Move the given RangeSearch model.
+   *
+   * @param other RangeSearch model to move.
+   */
+  RangeSearch& operator=(RangeSearch&& other);
 
   /**
    * Destroy the RangeSearch object.  If trees were created, they will be
diff --git a/src/mlpack/methods/range_search/range_search_impl.hpp b/src/mlpack/methods/range_search/range_search_impl.hpp
index 298aae995e..2652d47c89 100644
--- a/src/mlpack/methods/range_search/range_search_impl.hpp
+++ b/src/mlpack/methods/range_search/range_search_impl.hpp
@@ -169,25 +169,61 @@ template<typename MetricType,
                   typename TreeStatType,
                   typename TreeMatType> class TreeType>
 RangeSearch<MetricType, MatType, TreeType>&
-RangeSearch<MetricType, MatType, TreeType>::operator=(RangeSearch other)
+RangeSearch<MetricType, MatType, TreeType>::operator=(const RangeSearch& other)
 {
-  // Clean memory first.
-  if (treeOwner)
-    delete referenceTree;
-  if (naive)
-    delete referenceSet;
+  if (this != &other)
+  {
+    oldFromNewReferences = other.oldFromNewReferences;
+    referenceTree = other.referenceTree ? new Tree(*other.referenceTree) : nullptr;
+    referenceSet = other.referenceTree ? &referenceTree->Dataset() :
+        new MatType(*other.referenceSet);
+    treeOwner = other.referenceTree;
+    naive = other.naive;
+    singleMode = other.singleMode;
+    metric = other.metric;
+    baseCases = other.baseCases;
+    scores = other.scores;
+  }
+  return *this;
+}
 
-  // Move the other model.
-  oldFromNewReferences = std::move(other.oldFromNewReferences);
-  referenceTree = other.referenceTree;
-  referenceSet = other.referenceSet;
-  treeOwner = other.treeOwner;
-  naive = other.naive;
-  singleMode = other.singleMode;
-  metric = std::move(other.metric);
-  baseCases = other.baseCases;
-  scores = other.scores;
+template<typename MetricType,
+         typename MatType,
+         template<typename TreeMetricType,
+                  typename TreeStatType,
+                  typename TreeMatType> class TreeType>
+RangeSearch<MetricType, MatType, TreeType>&
+RangeSearch<MetricType, MatType, TreeType>::operator=(RangeSearch&& other)
+{
+  if (this != &other)
+  {
+    // Clean memory first.
+    if (treeOwner)
+      delete referenceTree;
+    if (naive)
+      delete referenceSet;
 
+    // Move the other model.
+    oldFromNewReferences = std::move(other.oldFromNewReferences);
+    referenceTree = other.referenceTree;
+    referenceSet = other.referenceSet;
+    treeOwner = other.treeOwner;
+    naive = other.naive;
+    singleMode = other.singleMode;
+    metric = std::move(other.metric);
+    baseCases = other.baseCases;
+    scores = other.scores;
+
+    // Clear other object.
+    other.referenceTree = nullptr;
+    other.referenceSet = nullptr;
+    other.treeOwner = false;
+    other.naive = false;
+    other.singleMode = false;
+    other.baseCases = 0;
+    other.scores = 0;
+
+  }
   return *this;
 }
 
@@ -254,12 +290,15 @@ void RangeSearch<MetricType, MatType, TreeType>::Train(
     throw std::invalid_argument("cannot train on given reference tree when "
         "naive search (without trees) is desired");
 
+  // Can only train when passed argument `referenceTree` is not nullptr
   if (treeOwner && referenceTree)
+  {
     delete this->referenceTree;
 
-  this->referenceTree = referenceTree;
-  this->referenceSet = &referenceTree->Dataset();
-  treeOwner = false;
+    this->referenceTree = referenceTree;
+    this->referenceSet = &referenceTree->Dataset();
+    treeOwner = false;
+  }
 }
 
 template<typename MetricType,