diff --git a/examples/metrics/metrics.go b/examples/metrics/metrics.go
index a1befd9..c8bc5f8 100644
--- a/examples/metrics/metrics.go
+++ b/examples/metrics/metrics.go
@@ -4,23 +4,27 @@ import (
 	"fmt"
 
 	pariwiseMetrics "github.com/sjwhitworth/golearn/metrics/pairwise"
-	"github.com/sjwhitworth/golearn/utilities"
 	mat "github.com/skelterjohn/go.matrix"
 )
 
 func main() {
-	randArray := utilities.RandomArray(3, 7)
-	vectorX := mat.MakeDenseMatrix(randArray, 1, 3)
-	randArray = utilities.RandomArray(3, 7)
-	vectorY := mat.MakeDenseMatrix(randArray, 1, 3)
+	vectorX := mat.MakeDenseMatrix([]float64{1, 2, 3}, 3, 1)
+	vectorY := mat.MakeDenseMatrix([]float64{3, 4, 5}, 3, 1)
 
-	distance, err := pariwiseMetrics.Euclidean(vectorX, vectorY)
+	euclidean := pariwiseMetrics.NewEuclidean()
+	polyKernel := pariwiseMetrics.NewPolyKernel(3)
 
+	euclideanDistance, err := euclidean.Distance(vectorX, vectorY)
+	polyKernelDistance, err := polyKernel.Distance(vectorX, vectorY)
 	if err != nil {
 		fmt.Println(err)
 		return
 	}
 
-	fmt.Println("Euclidean distance of " + vectorX.String() + " and " + vectorY.String() + " is: ")
-	fmt.Println(distance)
+	fmt.Println("Vector X:")
+	fmt.Println(vectorX.String())
+	fmt.Println("Vector Y: ")
+	fmt.Println(vectorY.String())
+	fmt.Println("Euclidean           : ", euclideanDistance)
+	fmt.Println("PolyKernel(degree 3): ", polyKernelDistance)
 }
diff --git a/metrics/pairwise/euclidean.go b/metrics/pairwise/euclidean.go
index cb594d1..bd8eddd 100644
--- a/metrics/pairwise/euclidean.go
+++ b/metrics/pairwise/euclidean.go
@@ -1,30 +1,32 @@
 package pairwise
 
 import (
-	"fmt"
+	"errors"
 	"math"
 
 	mat "github.com/skelterjohn/go.matrix"
 )
 
-// We may need to create Metrics / Vector interface for this
-func Euclidean(vectorX *mat.DenseMatrix, vectorY *mat.DenseMatrix) (float64, error) {
-	var sum float64
+type Euclidean struct{}
 
-	difference, err := vectorY.MinusDense(vectorX)
-
-	flat := difference.Array()
-
-	if err != nil {
-		fmt.Println(err)
-		return -1, err
-	}
-
-	for _, i := range flat {
-		squared := math.Pow(i, 2)
-		sum += squared
-	}
-
-	distance := math.Sqrt(sum)
-	return distance, nil
+func NewEuclidean() *Euclidean {
+	return &Euclidean{}
+}
+
+func (self *Euclidean) InnerProduct(vectorX *mat.DenseMatrix, vectorY *mat.DenseMatrix) (float64, error) {
+	if !CheckDimMatch(vectorX, vectorY) {
+		return 0, errors.New("Dimension mismatch")
+	}
+
+	result := mat.Product(mat.Transpose(vectorX), vectorY).Get(0, 0)
+
+	return result, nil
+}
+
+// We may need to create Metrics / Vector interface for this
+func (self *Euclidean) Distance(vectorX *mat.DenseMatrix, vectorY *mat.DenseMatrix) (float64, error) {
+	difference, err := vectorY.MinusDense(vectorX)
+	result, err := self.InnerProduct(difference, difference)
+
+	return math.Sqrt(result), err
 }
diff --git a/metrics/pairwise/pairwise.go b/metrics/pairwise/pairwise.go
new file mode 100644
index 0000000..a256038
--- /dev/null
+++ b/metrics/pairwise/pairwise.go
@@ -0,0 +1,20 @@
+package pairwise
+
+import (
+	mat "github.com/skelterjohn/go.matrix"
+)
+
+type Metric interface {
+	InnerProduct(vectorX *mat.DenseMatrix, vectorY *mat.DenseMatrix)
+	Distance(vectorX *mat.DenseMatrix, vectorY *mat.DenseMatrix)
+}
+
+func CheckDimMatch(vectorX *mat.DenseMatrix, vectorY *mat.DenseMatrix) bool {
+	if vectorX.Cols() != 1 ||
+		vectorY.Cols() != 1 ||
+		vectorX.Rows() != vectorY.Rows() {
+		return false
+	} else {
+		return true
+	}
+}
diff --git a/metrics/pairwise/poly_kernel.go b/metrics/pairwise/poly_kernel.go
new file mode 100644
index 0000000..2ed44da
--- /dev/null
+++ b/metrics/pairwise/poly_kernel.go
@@ -0,0 +1,34 @@
+package pairwise
+
+import (
+	"errors"
+	"math"
+
+	mat "github.com/skelterjohn/go.matrix"
+)
+
+type PolyKernel struct {
+	degree int
+}
+
+func NewPolyKernel(degree int) *PolyKernel {
+	return &PolyKernel{degree: degree}
+}
+
+func (self *PolyKernel) InnerProduct(vectorX *mat.DenseMatrix, vectorY *mat.DenseMatrix) (float64, error) {
+	if !CheckDimMatch(vectorX, vectorY) {
+		return 0, errors.New("Dimension mismatch")
+	}
+
+	result := mat.Product(mat.Transpose(vectorX), vectorY).Get(0, 0)
+	result = math.Pow(result+1, float64(self.degree))
+
+	return result, nil
+}
+
+func (self *PolyKernel) Distance(vectorX *mat.DenseMatrix, vectorY *mat.DenseMatrix) (float64, error) {
+	difference, err := vectorY.MinusDense(vectorX)
+	result, err := self.InnerProduct(difference, difference)
+
+	return math.Sqrt(result), err
+}