diff --git a/doc_classes/MLPPVector.xml b/doc_classes/MLPPVector.xml
index bfc97ec..da0eab7 100644
--- a/doc_classes/MLPPVector.xml
+++ b/doc_classes/MLPPVector.xml
@@ -29,7 +29,7 @@
 			<description>
 			</description>
 		</method>
-		<method name="add_mlpp_vector">
+		<method name="append_mlpp_vector">
 			<return type="void" />
 			<argument index="0" name="other" type="float" />
 			<description>
diff --git a/mlpp/gan/gan.cpp b/mlpp/gan/gan.cpp
index 7799c9a..798327c 100644
--- a/mlpp/gan/gan.cpp
+++ b/mlpp/gan/gan.cpp
@@ -65,7 +65,7 @@ void MLPPGAN::gradient_descent(real_t learning_rate, int max_epoch, bool ui) {
 		Ref<MLPPVector> y_hat = model_set_test_discriminator(discriminator_input_set);
 		Ref<MLPPVector> output_set = alg.zerovecnv(_n);
 		Ref<MLPPVector> output_set_real = alg.onevecnv(_n);
-		output_set->add_mlpp_vector(output_set_real); // Fake + real output scores.
+		output_set->append_mlpp_vector(output_set_real); // Fake + real output scores.
 
 		ComputeDiscriminatorGradientsResult dgrads = compute_discriminator_gradients(y_hat, _output_set);
 
diff --git a/mlpp/lin_alg/mlpp_vector.cpp b/mlpp/lin_alg/mlpp_vector.cpp
index ff0589d..31d9d70 100644
--- a/mlpp/lin_alg/mlpp_vector.cpp
+++ b/mlpp/lin_alg/mlpp_vector.cpp
@@ -36,7 +36,7 @@ void MLPPVector::push_back(real_t p_elem) {
 	_data[_size - 1] = p_elem;
 }
 
-void MLPPVector::add_mlpp_vector(const Ref<MLPPVector> &p_other) {
+void MLPPVector::append_mlpp_vector(const Ref<MLPPVector> &p_other) {
 	ERR_FAIL_COND(!p_other.is_valid());
 
 	int other_size = p_other->size();
@@ -899,7 +899,7 @@ void MLPPVector::absb(const Ref<MLPPVector> &a) {
 	}
 }
 
-Ref<MLPPVector> MLPPVector::zero_vec(int n) const {
+Ref<MLPPVector> MLPPVector::vecn_zero(int n) const {
 	Ref<MLPPVector> vec;
 	vec.instance();
 
@@ -908,7 +908,7 @@ Ref<MLPPVector> MLPPVector::zero_vec(int n) const {
 
 	return vec;
 }
-Ref<MLPPVector> MLPPVector::one_vec(int n) const {
+Ref<MLPPVector> MLPPVector::vecn_one(int n) const {
 	Ref<MLPPVector> vec;
 	vec.instance();
 
@@ -917,7 +917,7 @@ Ref<MLPPVector> MLPPVector::one_vec(int n) const {
 
 	return vec;
 }
-Ref<MLPPVector> MLPPVector::full_vec(int n, int k) const {
+Ref<MLPPVector> MLPPVector::vecn_full(int n, int k) const {
 	Ref<MLPPVector> vec;
 	vec.instance();
 
@@ -1360,7 +1360,7 @@ void MLPPVector::_bind_methods() {
 	ADD_PROPERTY(PropertyInfo(Variant::POOL_REAL_ARRAY, "data"), "set_data", "get_data");
 
 	ClassDB::bind_method(D_METHOD("push_back", "elem"), &MLPPVector::push_back);
-	ClassDB::bind_method(D_METHOD("add_mlpp_vector", "other"), &MLPPVector::push_back);
+	ClassDB::bind_method(D_METHOD("append_mlpp_vector", "other"), &MLPPVector::append_mlpp_vector);
 	ClassDB::bind_method(D_METHOD("remove", "index"), &MLPPVector::remove);
 	ClassDB::bind_method(D_METHOD("remove_unordered", "index"), &MLPPVector::remove_unordered);
 	ClassDB::bind_method(D_METHOD("erase", "val"), &MLPPVector::erase);
@@ -1450,9 +1450,9 @@ void MLPPVector::_bind_methods() {
 	ClassDB::bind_method(D_METHOD("absn"), &MLPPVector::absn);
 	ClassDB::bind_method(D_METHOD("absb", "a"), &MLPPVector::absb);
 
-	ClassDB::bind_method(D_METHOD("zero_vec", "n"), &MLPPVector::zero_vec);
-	ClassDB::bind_method(D_METHOD("one_vec", "n"), &MLPPVector::one_vec);
-	ClassDB::bind_method(D_METHOD("full_vec", "n", "k"), &MLPPVector::full_vec);
+	ClassDB::bind_method(D_METHOD("vecn_zero", "n"), &MLPPVector::vecn_zero);
+	ClassDB::bind_method(D_METHOD("vecn_one", "n"), &MLPPVector::vecn_one);
+	ClassDB::bind_method(D_METHOD("vecn_full", "n", "k"), &MLPPVector::vecn_full);
 
 	ClassDB::bind_method(D_METHOD("sin"), &MLPPVector::sin);
 	ClassDB::bind_method(D_METHOD("sinn"), &MLPPVector::sinn);
diff --git a/mlpp/lin_alg/mlpp_vector.h b/mlpp/lin_alg/mlpp_vector.h
index f2f094c..daea68e 100644
--- a/mlpp/lin_alg/mlpp_vector.h
+++ b/mlpp/lin_alg/mlpp_vector.h
@@ -33,7 +33,7 @@ public:
 	}
 
 	void push_back(real_t p_elem);
-	void add_mlpp_vector(const Ref<MLPPVector> &p_other);
+	void append_mlpp_vector(const Ref<MLPPVector> &p_other);
 
 	void remove(real_t p_index);
 
@@ -177,9 +177,9 @@ public:
 	Ref<MLPPVector> absn() const;
 	void absb(const Ref<MLPPVector> &a);
 
-	Ref<MLPPVector> zero_vec(int n) const;
-	Ref<MLPPVector> one_vec(int n) const;
-	Ref<MLPPVector> full_vec(int n, int k) const;
+	Ref<MLPPVector> vecn_zero(int n) const;
+	Ref<MLPPVector> vecn_one(int n) const;
+	Ref<MLPPVector> vecn_full(int n, int k) const;
 
 	void sin();
 	Ref<MLPPVector> sinn() const;
diff --git a/mlpp/wgan/wgan.cpp b/mlpp/wgan/wgan.cpp
index de67b2a..5d3defd 100644
--- a/mlpp/wgan/wgan.cpp
+++ b/mlpp/wgan/wgan.cpp
@@ -71,7 +71,7 @@ void MLPPWGAN::gradient_descent(real_t learning_rate, int max_epoch, bool ui) {
 			ly_hat = model_set_test_discriminator(discriminator_input_set);
 			loutput_set = alg.scalar_multiplynv(-1, alg.onevecnv(_n)); // WGAN changes y_i = 1 and y_i = 0 to y_i = 1 and y_i = -1
 			Ref<MLPPVector> output_set_real = alg.onevecnv(_n);
-			loutput_set->add_mlpp_vector(output_set_real); // Fake + real output scores.
+			loutput_set->append_mlpp_vector(output_set_real); // Fake + real output scores.
 
 			DiscriminatorGradientResult discriminator_gradient_results = compute_discriminator_gradients(ly_hat, loutput_set);
 			Vector<Ref<MLPPMatrix>> cumulative_discriminator_hidden_layer_w_grad = discriminator_gradient_results.cumulative_hidden_layer_w_grad;