Accord.Tests.MachineLearning.SequentialMinimalOptimizationTest.TransformTest C# (CSharp) Method

        public void TransformTest()
        {
            var inputs = yinyang.Submatrix(null, 0, 1).ToJagged();
            var labels = yinyang.GetColumn(2).ToInt32();

            ConfusionMatrix actual, expected;
            SequentialMinimalOptimization a, b;

            var kernel = new Polynomial(2, 0);

            {
                var machine = new KernelSupportVectorMachine(kernel, inputs[0].Length);
                a = new SequentialMinimalOptimization(machine, inputs, labels);
                a.UseComplexityHeuristic = true;
                a.Run();

                int[] values = new int[labels.Length];
                for (int i = 0; i < values.Length; i++)
                    values[i] = Math.Sign(machine.Compute(inputs[i]));

                expected = new ConfusionMatrix(values, labels);
            }

            {
                var projection = inputs.Apply(kernel.Transform);
                var machine = new SupportVectorMachine(projection[0].Length);
                b = new SequentialMinimalOptimization(machine, projection, labels);
                b.UseComplexityHeuristic = true;
                b.Run();

                int[] values = new int[labels.Length];
                for (int i = 0; i < values.Length; i++)
                    values[i] = Math.Sign(machine.Compute(projection[i]));

                actual = new ConfusionMatrix(values, labels);
            }

            Assert.AreEqual(a.Complexity, b.Complexity, 1e-15);
            Assert.AreEqual(expected.TrueNegatives, actual.TrueNegatives);
            Assert.AreEqual(expected.TruePositives, actual.TruePositives);
            Assert.AreEqual(expected.FalseNegatives, actual.FalseNegatives);
            Assert.AreEqual(expected.FalsePositives, actual.FalsePositives);
        }