Minor changes in names and extracted method, etc.

src/machine_learning/Vector.java

@@ -34,7 +34,7 @@ public class Vector
 
     public Vector add(Vector b)
     {
-        if (this.dimension() != b.dimension()) throw new IllegalArgumentException("Dimensions must be equals.");
+        checkEqualDimensions(b);
         return new Vector(IntStream.range(0,
                 this.dimension())
                 .mapToObj(i -> this.get(i) + b.get(i))
@@ -45,7 +45,7 @@ public class Vector
 
     public Vector subtract(Vector b)
     {
-        if (this.dimension() != b.dimension()) throw new IllegalArgumentException("Dimensions must be equals.");
+        checkEqualDimensions(b);
         return new Vector(IntStream.range(0,
                 this.dimension())
                 .mapToObj(i -> this.get(i) - b.get(i))
@@ -55,7 +55,7 @@ public class Vector
 
     public double scalar(Vector b)
     {
-        if (this.dimension() != b.dimension()) throw new IllegalArgumentException("Dimensions must be equals.");
+        checkEqualDimensions(b);
         return IntStream.range(0,
                 this.dimension())
                 .mapToDouble(i -> this.get(i) * b.get(i))
@@ -80,14 +80,9 @@ public class Vector
 
     public Vector divide(double div)
     {
-        var divided = new ArrayList<Double>();
+        return new Vector(IntStream.range(0, this.dimension())
-
+                .mapToObj(i -> this.values.get(i) / div)
-        for (int i = 0; i < this.dimension(); i++)
+                .collect(Collectors.toCollection(ArrayList::new)));
-        {
-            divided.add(this.values.get(i) / div);
-        }
-
-        return new Vector(divided);
     }
 
     public double get(int index)
@@ -133,4 +128,10 @@ public class Vector
     {
         return this.values.toString();
     }
+
+    private void checkEqualDimensions(Vector b)
+    {
+        if (this.dimension() != b.dimension())
+            throw new IllegalArgumentException("Dimensions must be equal");
+    }
 }

src/machine_learning/nearest_neighbour/DistanceFunction.java

@@ -2,7 +2,7 @@ package machine_learning.nearest_neighbour;
 
 import machine_learning.Vector;
 
-public interface Distance
+public interface DistanceFunction
 {
     double distance(Vector a, Vector b);
 }

src/machine_learning/nearest_neighbour/KNearestNeighbour.java

@@ -15,18 +15,18 @@ public class KNearestNeighbour implements MachineLearning
     private List<Vector> positives;
     private List<Vector> negatives;
 
-    private final Distance distance;
+    private final DistanceFunction distanceFunction;
 
     private final int k;
 
-    public KNearestNeighbour(Distance distance)
+    public KNearestNeighbour(DistanceFunction distanceFunction)
     {
-        this(distance, 1);
+        this(distanceFunction, 1);
     }
 
-    public KNearestNeighbour(Distance distance, int k)
+    public KNearestNeighbour(DistanceFunction distanceFunction, int k)
     {
-        this.distance = distance;
+        this.distanceFunction = distanceFunction;
         this.k = k;
     }
 
@@ -67,7 +67,7 @@ public class KNearestNeighbour implements MachineLearning
     private List<Vector> nearestNeighbours(List<Vector> vectors, Vector vector)
     {
         return vectors.parallelStream()
-                .map(v -> Map.entry(this.distance.distance(v, vector), v))
+                .map(v -> Map.entry(this.distanceFunction.distance(v, vector), v))
                 .sorted((e1, e2) -> e1.getKey() >= e2.getKey() ? (e1.getKey().equals(e2.getKey()) ? 0 : 1) : -1)
                 .map(Map.Entry::getValue)
                 .collect(Collectors.toList())

test/machine_learning/nearest_neighbour/KNearestNeighbourTest.java

@@ -22,8 +22,9 @@ import static org.junit.jupiter.api.Assertions.*;
 @TestInstance(TestInstance.Lifecycle.PER_CLASS)
 class KNearestNeighbourTest
 {
-    List<Vector> positives;
+    private List<Vector> positives;
-    List<Vector> negatives;
+    private List<Vector> negatives;
+    private DistanceFunction distanceFunction;
 
     @BeforeAll
     void initLearnData()
@@ -41,12 +42,14 @@ class KNearestNeighbourTest
                 new Vector(8d, 2d),
                 new Vector(9d, 0d))
         );
+
+        this.distanceFunction = (a, b) -> Math.abs(a.get(0) - b.get(0)) + Math.abs(a.get(1) - b.get(1));
     }
 
     @Test
     public void shouldReturnCorrectClassForVectorWithKEquals3()
     {
-        var kNearestNeighbour = new KNearestNeighbour((a ,b) -> Math.abs(a.get(0) - b.get(0)) + Math.abs(a.get(1) - b.get(1)), 3);
+        var kNearestNeighbour = new KNearestNeighbour(this.distanceFunction, 3);
         kNearestNeighbour.learn(this.positives, this.negatives);
         var vector = new Vector(8, 3.5);
 
@@ -59,7 +62,7 @@ class KNearestNeighbourTest
     @Test
     public void shouldReturnCorrectClassForVectorWithKEquals5()
     {
-        var kNearestNeighbour = new KNearestNeighbour((a ,b) -> Math.abs(a.get(0) - b.get(0)) + Math.abs(a.get(1) - b.get(1)), 5);
+        var kNearestNeighbour = new KNearestNeighbour(this.distanceFunction, 5);
         kNearestNeighbour.learn(this.positives, this.negatives);
         var vector = new Vector(8, 3.5);