Added classify method for perceptron

src/machine_learning/perceptron/Perceptron.java

@@ -1,6 +1,7 @@
 package machine_learning.perceptron;
 
 import machine_learning.Vector;
+import machine_learning.nearest_neighbour.DataClass;
 
 import java.util.List;
 
@@ -42,6 +43,11 @@ public class Perceptron
         System.out.println("-----------------------------------------------------------------");
     }
 
+    public DataClass classify(Vector vector)
+    {
+        return this.weight.scalar(vector) > 0 ? DataClass.POSITIVE : DataClass.NEGATIVE;
+    }
+
     private Vector getInitializationVector(List<Vector> positives, List<Vector> negatives)
     {
         var a = new Vector(positives.get(0).dimension());

test/machine_learning/perceptron/PerceptronTest.java

@@ -1,6 +1,8 @@
 package machine_learning.perceptron;
 
 import machine_learning.Vector;
+import machine_learning.nearest_neighbour.DataClass;
+import org.junit.jupiter.api.Assertions;
 import org.junit.jupiter.api.BeforeAll;
 import org.junit.jupiter.api.Test;
 import org.junit.jupiter.api.TestInstance;
@@ -8,11 +10,14 @@ import org.junit.jupiter.api.TestInstance;
 import java.util.ArrayList;
 import java.util.List;
 
+import static org.junit.jupiter.api.Assertions.*;
+
 @TestInstance(TestInstance.Lifecycle.PER_CLASS)
 class PerceptronTest
 {
     List<Vector> positives;
     List<Vector> negatives;
+    Perceptron perceptron;
 
     @BeforeAll
     void initLearnData()
@@ -31,11 +36,30 @@ class PerceptronTest
                 new Vector(8d, 2d, biasUnit),
                 new Vector(9d, 0d, biasUnit))
         );
+
+        this.perceptron = new Perceptron();
+        this.perceptron.learn(this.positives, this.negatives);
     }
 
     @Test
-    void shouldClassifyCorrect()
+    void shouldClassifyVectorCorrectAsNegative()
     {
-        new Perceptron().learn(this.positives, this.negatives);
+        var vector = new Vector(0d, 0d, 1d);
+
+        var actualClass = this.perceptron.classify(vector);
+        var expectedClass = DataClass.NEGATIVE;
+
+        assertEquals(expectedClass, actualClass);
+    }
+
+    @Test
+    void shouldClassifyVectorCorrectAsPositive()
+    {
+        var vector = new Vector(9d, 3d, 1d);
+
+        var actualClass = this.perceptron.classify(vector);
+        var expectedClass = DataClass.POSITIVE;
+
+        assertEquals(expectedClass, actualClass);
     }
 }