Accord.Tests.MachineLearning.LinearCoordinateDescentTest.ComputeTest5 C# (CSharp) Метод

        public void ComputeTest5()
        {
            var dataset = SequentialMinimalOptimizationTest.yinyang;

            double[][] inputs = dataset.Submatrix(null, 0, 1).ToJagged();
            int[] labels = dataset.GetColumn(2).ToInt32();

            var kernel = new Polynomial(2, 1);

            Accord.Math.Tools.SetupGenerator(0);
            var projection = inputs.Apply(kernel.Transform);
            var machine = new SupportVectorMachine(projection[0].Length);
            var smo = new LinearCoordinateDescent(machine, projection, labels)
            {
                Complexity = 1000000,
                Tolerance = 1e-15
            };

            double error = smo.Run();

            Assert.AreEqual(1000000.0, smo.Complexity, 1e-15);

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

            ConfusionMatrix matrix = new ConfusionMatrix(actual, labels);
            Assert.AreEqual(6, matrix.FalseNegatives);
            Assert.AreEqual(7, matrix.FalsePositives);
            Assert.AreEqual(44, matrix.TruePositives);
            Assert.AreEqual(43, matrix.TrueNegatives);
        }