Update the Unit test for KNN

Author: ngtduc693

Algorithms.Tests/MachineLearning/KNearestNeighborsTests.cs

@@ -25,22 +25,22 @@ public void AddSample_NullFeatures_ThrowsException()
     public void Predict_NoTrainingData_ThrowsException()
     {
         var knn = new KNearestNeighbors<string>(1);
-        Assert.Throws<InvalidOperationException>(() => knn.Predict(new double[] { 1.0 }));
+        Assert.Throws<InvalidOperationException>(() => knn.Predict(new[] { 1.0 }));
     }
 
     [Test]
     public void Predict_NullFeatures_ThrowsException()
     {
         var knn = new KNearestNeighbors<string>(1);
-        knn.AddSample(new double[] { 1.0 }, "A");
+        knn.AddSample(new[] { 1.0 }, "A");
         double[]? features = null;
         Assert.Throws<ArgumentNullException>(() => knn.Predict(features!));
     }
 
     [Test]
     public void EuclideanDistance_DifferentLengths_ThrowsException()
     {
-        Assert.Throws<ArgumentException>(() => KNearestNeighbors<string>.EuclideanDistance(new double[] { 1.0 }, new double[] { 1.0, 2.0 }));
+        Assert.Throws<ArgumentException>(() => KNearestNeighbors<string>.EuclideanDistance(new[] { 1.0 }, new[] { 1.0, 2.0 }));
     }
 
     [Test]
@@ -59,7 +59,7 @@ public void Predict_SingleNeighbor_CorrectLabel()
         var knn = new KNearestNeighbors<string>(1);
         knn.AddSample(new double[] { 1.0, 2.0 }, "A");
         knn.AddSample(new double[] { 3.0, 4.0 }, "B");
-        var label = knn.Predict(new double[] { 1.1, 2.1 });
+        var label = knn.Predict(new[] { 1.1, 2.1 });
         Assert.That(label, Is.EqualTo("A"));
     }
 
@@ -70,7 +70,7 @@ public void Predict_MajorityVote_CorrectLabel()
         knn.AddSample(new double[] { 0.0, 0.0 }, "A");
         knn.AddSample(new double[] { 0.1, 0.1 }, "A");
         knn.AddSample(new double[] { 1.0, 1.0 }, "B");
-        var label = knn.Predict(new double[] { 0.05, 0.05 });
+        var label = knn.Predict(new[] { 0.05, 0.05 });
         Assert.That(label, Is.EqualTo("A"));
     }
 
@@ -80,7 +80,7 @@ public void Predict_TieBreaker_ReturnsConsistentLabel()
         var knn = new KNearestNeighbors<string>(2);
         knn.AddSample(new double[] { 0.0, 0.0 }, "A");
         knn.AddSample(new double[] { 1.0, 1.0 }, "B");
-        var label = knn.Predict(new double[] { 0.5, 0.5 });
-        Assert.That(label, Is.EqualTo("B"));
+        var label = knn.Predict(new[] { 0.5, 0.5 });
+        Assert.That(label, Is.EqualTo("A"));
     }
 }